Evidence and Citation Pack

This document maps the Royalty Driven LLM mechanism to existing systems, standards, research, and policy signals.

Existing Creator Revenue Model

YouTube's Partner Program is a practical analogy, not a scope limit. YouTube says creators can earn ad revenue shares from ads on their videos, with a 55% share for long-form videos and 45% for Shorts. The Royalty Driven LLM prototype borrows the idea of a fixed creator pool, but replaces video views with auditable AI usage events that can occur inside any AI application or model provider.

Source: YouTube Official Blog, "YouTube Partner Program, Explained" (2025).

Existing Rights-Claim Model

YouTube Content ID is evidence that large-scale content identification and rights management can operate inside a consumer platform. YouTube describes Content ID as an automated system that scans uploaded videos against copyright-owner reference files and can block, monetize, share revenue, or track viewership.

Source: YouTube Help, "How Content ID works."

Data Valuation Research

Data Shapley provides a principled research basis for valuing individual training data points. Ghorbani and Zou define Data Shapley as a metric for quantifying the value of each training datum to predictor performance and argue that it satisfies natural properties of equitable data valuation. Recent LLM-scale valuation and privacy-preserving valuation work extends that basis: DATE-LM benchmarks attribution methods across LLM tasks, RISE and LoRIF make influence evidence more scalable, Concept Influence attributes behavior to semantic directions, and ZK-Value demonstrates a zero-knowledge path for verifiable data valuation. RDLLM-L95 uses those methods as possible evidence channels for residual corpus royalty, while still requiring license checks, direct-attribution exclusion, creator-level caps, payout-or-escrow conservation, and creator receipts. RDLLM-L96 adds an explicit valuation-method audit so those methods must also pass benchmark, anti-document, duplicate-guard, calibration, stability, method-commitment, and privacy-commitment checks before residual royalties are trusted. RDLLM-L97 adds exact evidence-region binding: visible claim spans and source-footer rows must point to the page, line, character range, bounding box, or timecode that actually supports the answer, and neighboring wrong-region controls must fail. RDLLM-L98 adds source access leases: directly settled consumed source rows must carry creator-issued active lease signatures, matching hash-only access logs, license-contract permission, and exact region binding; denied or unleased use must remain in escrow. RDLLM-L99 adds content-protocol ingestion: external publisher signals such as RSL, CoMP, SCP, ODRL, Croissant, robots.txt, and C2PA/TDM reservations must be hash-preserved and carried into RDLLM creator contracts, source-access leases, and escrow routing before direct settlement. RDLLM-L100 adds citation reliance receipts: visible footer sources must be bound to pre-generation evidence locks, rendered claim-evidence rows, claim-source replay, causal utility trials, current-turn trace membership, source-access leases, and content-protocol permission before direct settlement. RDLLM-L101 adds license transaction receipts: directly settled source rows must also have a signed license-server authorization token, license-ledger inclusion, access-log binding, protocol-term match, and validity window before access. A missing, expired, unsigned, non-ledgered, or access-mismatched token forces settlement to review or escrow. RDLLM-L102 adds grounded source footer receipts: the exact source footer shown to the user must compile source-confidence rows, availability and inspectability rows, public evidence-region bindings, citation-reliance receipts, license transaction receipts, and hash-only verifier handles before it can claim that an answer is grounded. RDLLM-L103 adds source footer delivery receipts: the grounded footer must survive into the proof-carrying response, copied output, serving-gateway egress hash, source labels, claim span handles, and client-visible verifier metadata before a client can render or relay the answer as verified. RDLLM-L104 adds foundation API attribution profiles: a generic model client must receive minimum attribution headers, embedded proof objects, well-known verifier paths, verifier commands, and fail-closed policies before it can treat an answer as attributed rather than merely decorated with citations. RDLLM-L105 adds client attribution enforcement receipts: the relying client must prove it observed the L104 headers, replayed the embedded response envelope and source-footer-delivery receipt, matched source labels to delivered rows, and failed closed before rendering an attributed answer. RDLLM-L106 adds persistent memory provenance receipts: assistant, agent, or model memory cells must preserve origin source labels, upstream proof hashes, license and retention policy, royalty carry-forward rows, and visible footer labels when that memory is reused in a later answer. RDLLM-L107 adds private reasoning attribution receipts: hidden scratchpads, sub-agent handoffs, router synthesis, and memory-influenced reasoning must publish hash commitments to their private trace, bind upstream proof hashes, carry source labels into the verified footer, and preserve royalty rows without exposing chain-of-thought. RDLLM-L108 adds post-training signal provenance receipts: RLHF, RLAIF, RLVR, preference, reward, verifier, and critique signals must bind to L107 private reasoning receipts and L91 model-lineage reports, disclose synthetic signal use, preserve source labels and royalty obligations, and publish attested hash commitments without exposing raw feedback, prompt, answer, source, or reward text. RDLLM-L109 adds attribution bills of materials: model releases must publish a CycloneDX-aligned rdllm-attribution-bom/v1 artifact that binds model identity, source components, notice hashes, license-term hashes, proof artifacts, post-training signal provenance, the provider card, and the proof-dependency graph without exposing raw source, feedback, prompt, answer, notice, license, or payment text. RDLLM-L110 adds creator attribution audit indexes: creator-side queries must replay across model-release ABOM rows, grounded footers, source-footer delivery, post-training signals, source-access leases, license transactions, model lineage, training summaries, and payout receipts using namespaced source identities and privacy-preserving proof handles rather than raw private text. RDLLM-L111 adds creator attribution audit federations: the same creator/work/hash query can be replayed across multiple provider-local L110 indexes under one query commitment, with provider-scoped source-label namespaces, bound federation or exchange artifacts, and explicit rejection of query drift, duplicate provider identities, unresolved cross-provider creator identity conflicts, and private text leakage. RDLLM-L112 adds creator audit federation transparency: the L111 federation answer and every participant index hash must appear in append-only transparency logs with valid inclusion proofs, prefix consistency, split-view detection, and same-query equivocation detection before the federation can be treated as industry-grade source confidence evidence. RDLLM-L113 adds creator audit transparency monitors: a creator or auditor can scan the L112 logs for a query commitment, prove each matching entry's inclusion, see newly observed federation or participant-index appearances since the prior monitor run, and reject contradictory same-query answers without exposing the raw creator, work, prompt, answer, source, license, or payment text. RDLLM-L114 adds creator audit private watch receipts: an L113 monitor can be converted into keyed watch tokens so a creator can prove appearances and new observations to an authorized auditor without publishing stable query hashes, provider-set hashes, federation hashes, participant-index hashes, provider IDs, prompt text, answer text, source text, license text, or payment data. RDLLM-L115 adds deep-research citation audits: rendered long-form answers are parsed for citation markers, each marker must resolve to a materialized source row, each cited claim must clear relevance and factual-support thresholds, and link-only or source-looking citations fail when the source does not support the specific claim. RDLLM-L116 adds source freshness audits: every static, current, latest, recent, rapidly changing, or as-of claim is classified; dynamic claims must use sources with retrieved-at and effective-at metadata, valid-at-answer-time windows, source-version hashes, freshness limits, retrieval-lag limits, and no ignored fresher supported candidate. RDLLM-L117 adds royalty-abuse audits: before direct settlement, public hash-only reports must show that source-farm signals, sybil or linked creator accounts, duplicate-source clusters, reciprocal boosting, undisclosed synthetic sources, and direct-payout concentration are either absent or routed to abuse-review escrow. RDLLM-L118 adds consent revocation propagation audits: after an opt-out, revocation, lease expiry, or license change, public hash-only reports must show that the changed rights state propagated to retrieval indexes, source-access leases, license transactions, grounded source footers, source-footer delivery, persistent memory, private reasoning, post-training signals, attribution exchange, creator audit surfaces, downstream providers, and settlement before future use or direct payout can continue. Historical usage event hashes are preserved rather than rewritten. RDLLM-L119 adds evidence-force calibration audits: each cited claim's wording is ranked against the cited evidence across relation, modality, scope, temporal, and numeric force. A citation can be real, fresh, licensed, and relevant but still fail if the answer turns weak evidence into certainty, local evidence into universal scope, or approximate evidence into exact numbers. The audit now also binds the signed citation-footer contract's visible claim rows to force rows, so verified footers cannot omit calibration for displayed claims. Verified footers and direct settlement require the claim force to be no stronger than the evidence force. RDLLM-L120 adds warranted source footers: the public footer exposes the relation, modality, scope, temporal, and numeric warrant labels for every visible verified footer claim. Users see why a source warrants the answer wording, while verifiers replay the labels against L119 without revealing raw prompt, claim, source, or evidence text. RDLLM-L121 adds source-origin lineage reports: before a visible source can receive direct payout, the provider must show trusted human-origin attestation or synthetic-with-lineage upstream splits. Unknown-origin or unattributed synthetic sources remain visible as source rows but route settlement to origin-review escrow, preventing AI-generated wrapper pages from laundering attribution away from the original creators. RDLLM-L122 adds evidence-preview footers: every verified visible claim must carry a short, permissioned source snippet, source URL, warrant label, origin label, and proof hash. This gives users inspectable grounding in the footer while preserving full source text, prompt, answer, private reasoning, and payment privacy. RDLLM-L123 adds evidence-locator manifests: every public evidence preview must resolve to an exact locator URL, resolver status, and snapshot or text-fragment proof. This makes the footer click-through verifiable without redisclosing raw source or excerpt text. RDLLM-L124 adds citation URL-health reports: every public locator must be live, content-addressed, DOI-resolved, or backed by archival snapshot evidence. Fabricated, never-seen, mismatched, or unverified locator URLs fail closed before they can appear as trusted response footers. RDLLM-L125 adds composite foundation adapter reports: native OpenAI Responses, Anthropic Messages, Google Gemini, Meta/Llama-style, Mistral, Cohere, xAI, Amazon Bedrock Converse, Azure OpenAI Responses, and OpenAI-compatible response objects must map their native output hash, response identity, model identity, attribution headers, JSON proof fields, citation/tool paths, streaming final-event hashes, and fail-closed policy to the same RDLLM response envelope, source-footer-delivery receipt, and citation URL-health report before a provider can claim a grounded answer. RDLLM-L126 adds foundation provider conformance matrices: each provider family must publish hash-only positive and negative fixtures proving sync response, streaming, tool, citation/grounding, URL-health, structured proof-field, claim-support-footer, parametric-memory-fallback, and fail-closed behavior. RDLLM-L127 adds foundation runtime adapter receipts: a concrete native provider response must either normalize into the RDLLM proof contract with matching headers, JSON proof fields, streaming final hashes, citation/tool paths, URL-health evidence, and source-footer bindings, or fail closed before display. RDLLM-L128 adds foundation runtime router receipts: multi-provider routers must prove every candidate provider family is adapter-backed, conformance-backed, hash-committed, and fail-closed, and that the selected route binds to a released L127 runtime adapter. RDLLM-L129 adds foundation model deployment attestations: the selected route must bind to an active provider deployment key, signed opaque model/version commitments, and request/response boundary hashes before a provider can release a foundational-model answer. RDLLM-L130 adds universal composition receipts: when one public answer is assembled from multiple foundation providers, every provider segment must bind to exactly one L129 deployment attestation, preserve source-footer obligations, expose hash-only telemetry span commitments, and conserve provider weights before display. RDLLM-L131 adds universal composition settlement receipts: when the displayed answer already carries L130 provider segments and delivered source footers, each segment's source labels and claim IDs must reconcile to source-entitlement rows and creator obligations. The receipt binds the L130 composition hash, response envelope hash, source-footer delivery hash, revenue allocation report, optional clearinghouse report, source-entitlement weights, payable rows, escrow rows, and held rows. It fails closed if visible source rows are dropped, if a segment's source-entitlement weights do not sum to one, if creator-pool totals drift, or if unresolved, disputed, blocked, or revoked sources receive direct payment. RDLLM-L132 adds universal foundation model contracts: before a provider, broker, agent host, or customer can treat a foundation-model response as RDLLM verified, one signed contract must bind the provider card, integration profile, discovery manifest, proof dependency graph, L125-L131 adapter/conformance/runtime/router/ deployment/composition/settlement artifacts, selected route, public source footer, settlement proof, and every required provider family. It fails closed when a provider family is missing, public surfaces are not published, the selected route does not bind to runtime and deployment proofs, the L131 settlement is not ready, or private prompt/output/source/payment text leaks. RDLLM-L133 adds universal invocation guards: before a concrete native provider call is made, the gateway must prove the L132 contract is ready, the selected route and deployment attestation match, request-projection and response-binding hashes match, required pre-call headers are present, the source-footer delivery and response-envelope hashes are bound, and GenAI telemetry names the same provider, request model, response model, contract hash, route ID, and request projection hash. Missing headers, route drift, boundary drift, unready L132 contracts, missing source-footer requirements, telemetry drift, or private text leakage block the native call. RDLLM-L134 adds universal invocation coverage: provider meter logs, gateway egress logs, L133 guard receipts, source-footer delivery hashes, response-envelope hashes, and invoice rows must reconcile one-to-one across the deployment. An unguarded provider meter event, duplicate guard, missing gateway row, source-footer or envelope gap, invoice drift, gross-revenue mismatch, or private text leakage blocks coverage certification. RDLLM-L135 adds universal invocation witnesses: every L134-covered native provider call must bind to a provider-signed usage receipt, independently observed egress event, and independent witness quorum. Missing provider receipts, missing egress observations, witness-quorum gaps, provider/egress field drift, or private text leakage blocks non-repudiation. RDLLM-L136 adds universal content credentials: every released or copied output must bind visible source-footer rows, permissioned evidence previews, exact locator rows, URL-health rows, creator payout eligibility, output content credential assertions, durable watermark/fingerprint signals, public verifier surfaces, and the L135 invocation witness. Missing footer rows, weak citation URL health, missing payout rows, absent content credentials, missing durable signals, weak provider-call non-repudiation, or private text leakage blocks publication.

Source: Ghorbani and Zou, "Data Shapley: Equitable Valuation of Data for Machine Learning" (ICML 2019); Jiao et al., "DATE-LM" (NeurIPS Datasets and Benchmarks 2025); Ran et al., "RISE" (2026); Li et al., "LoRIF" (2026); Kowal et al., "Concept Influence" (2026); Wang et al., "ZK-Value" (2026); Panchigar et al., "Synthetic Sources?" (2026); Qian et al., "Relevant Is Not Warranted" (2026); "Sovereign Context Protocol" (2026); Wallat et al., "Correctness is not Faithfulness in Retrieval Augmented Generation Attributions" (ICTIR 2025); Shi et al., "CiteAudit" (2026); Yu et al., "TRACER" (2026); AEX Framework (2026); RSL Standard (2025); IETF SCITT/RFC 9943 (2026); Onweller et al., "Cited but Not Verified" (2026); Nematov et al., "Source Attribution in Retrieval-Augmented Generation" (2025); Jain and Vedam, "CUE-R" (2026); RecencyQA (2026); FreshLLMs/FreshQA (2023); DynaRAG (2026); "The Attribution Crisis in LLM Search Results" (Data & Policy 2026); "GAD in the Wild" (2026). AEX Framework for LLM APIs (2026); OpenAI, "Advancing Content Provenance" (2026); Borro et al., "Memori" (2026); Model Context Protocol Specification (2025); Huang et al., "RLVR Datasets and Where to Find Them" (2026); Li et al., "Tracing the Roots" (2026); Qiu et al., "Provable Model Provenance Set for Large Language Models" (2026); CycloneDX AI/ML-BOM (2026); AIBOM (2026); Permissive-Washing (2026); Foundation Model Transparency Index (2026); C2PA Content Credentials (2026); W3C Verifiable Credentials/Data Integrity (2025); OpenID Federation 1.0 (2024).

Recent Grounding and Citation Research

Recent source-attribution work shows why the mechanism now treats citations as first-class user-facing evidence rather than a cosmetic appendix. AIS defines a framework for checking whether generated statements are attributable to identified sources. ALCE evaluates generated answers along fluency, correctness, and citation quality. RECLAIM and Think&Cite push toward sentence-level attributed generation, while C2-Cite argues that citation markers should behave like active source pointers instead of generic bracket tokens. Newer span-level diagnostics show that document overlap does not guarantee evidence continuity, so RDLLM now records exact evidence span hashes for supported claims. The L97 evidence-region binding layer extends this from "a supporting document was found" to "this rendered claim and footer row bind to this exact source location."

Recent diagnostic work also shows why retrieval alone is insufficient. RAGChecker uses fine-grained diagnostics for retrieval and generation failures. MedRAGChecker uses claim-level biomedical verification. LUMINA studies hallucinations that remain even with retrieved context, caused by the tension between external context and internal model knowledge. "Cited but Not Verified" evaluates source attribution in LLM deep-research agents by checking link validity, content relevance, and factual support; it reports that even strong systems can maintain high link validity while fact support remains much lower. The 2026 "LLM hallucinations in the wild" paper shows that fabricated citations are already leaking into scholarly literature at scale. SourceBench adds a source-quality lens for AI-cited web pages, including relevance, factual accuracy, objectivity, freshness, authority/accountability, and clarity. LegalCiteBench shows that citation recovery and verification are especially brittle in law, where plausible but wrong authorities can cause professional harm. Dependable RAG work on factual confidence prediction argues that systems need confidence measures for whether retrieved chunks really support generated answers. New 2026 scientific-citation and evidence-ranking work strengthens the same design choice. CiteCheck and CiteAudit verify whether generated citations resolve to real works and faithful metadata, while user-centric evidence ranking and SciTrue show that claim verification needs evidence ordered for human inspection and explicit source-level traceability. DAVinCI adds the same lesson from another angle: claim inference should combine attribution to internal/external evidence with entailment-based verification and confidence calibration before users trust the answer. Recent citation-faithfulness and prompt-injection work adds a stricter boundary: supporting source text cannot be trusted as instructions. Wallat et al. distinguish correct citations from faithful reliance on cited documents; CiteGuard validates citation-attribution alignment through retrieval-aware checks; OWASP LLM01:2025 recommends segregating external content; AIP shows that RAG prompts can be weaponized; and large-scale 2026 measurements find indirect prompt injections in web content. RDLLM-L60 proves cited evidence was in the generation context before answer delivery, RDLLM-L61 proves that those source packets were evidence-only data, not instruction/control channels or attribution/payout policy inputs, and RDLLM-L62 proves that answer claims, footer rows, payout participation, and release decisions are influenced only by authorized proof, policy, accounting, and boundary-guard artifacts. This also motivates private audit challenges: the user-facing footer can expose source identity, confidence, and span hashes, while authorized auditors can test the redacted receipt paths for evidence text, access traces, rights decisions, and royalty allocation without publishing the underlying private values.

Sources: Rashkin et al. (AIS, 2023); Gao et al. (ALCE, 2023); Xia et al. (RECLAIM, 2025); Li and Ng (Think&Cite, 2025); Yu et al. (C2-Cite, 2026); Ponnuraj (retrieval jitter, 2026); Ru et al. (RAGChecker, 2024); Ji et al. (MedRAGChecker, 2026); Yeh et al. (LUMINA, 2026); Onweller et al. (Cited but Not Verified, 2026); Zhao et al. (LLM hallucinations in the wild, 2026); Jin et al. (SourceBench, 2026); Chen et al. (LegalCiteBench, 2026); Geissler et al. (factual confidence prediction, 2026); Khajavi et al. (CiteCheck, 2026); Shi et al. (CiteAudit, 2026); Alt et al. (user-centric evidence ranking, 2026); Tan et al. (SciTrue, 2026); Rawte et al. (DAVinCI, 2026); Wallat et al. (citation faithfulness, 2025); Choi et al. (CiteGuard, 2026); OWASP LLM01:2025; Chaturvedi et al. (AIP, EMNLP 2025); Khodayari et al. (indirect prompt injection in the wild, 2026).

Training Influence Research

Influence functions and TracIn support the idea that model predictions can be traced back to influential training examples, though this is approximate at LLM scale. Koh and Liang use influence functions to trace a prediction back to training data. Pruthi et al. introduce TracIn, a checkpoint-and-gradient method for estimating training-data influence.

Sources: Koh and Liang (ICML 2017); Pruthi et al. (NeurIPS 2020).

New 2026 training-provenance work strengthens the case for separating output attribution from generic correctness. DataDignity frames this as "pinpoint provenance": given a prompt, response, and candidate corpus, rank the documents that best support the response. DebugLM proposes models that learn provenance tags for training data sources and can trace behaviors to responsible datasets. RDLLM uses a lighter runtime version of the same idea: every usage event must preserve which candidate works supported, failed to support, or were blocked from settlement.

Sources: Li, Banburski-Fahey, and Lanier, "DataDignity: Training Data Attribution for Large Language Models" (2026); Mo et al., "DebugLM: Learning Traceable Training Data Provenance for LLMs" (2026).

Recent RAG attribution work adds a stricter requirement: a source should not only look semantically relevant; it should be tested for utility and marginal influence. Source Attribution in Retrieval-Augmented Generation adapts Shapley-style document attribution to identify influential retrieved documents under cost constraints. Who Benefits from RAG? separates exposure, utility, and attribution bias. 2026 counterfactual RAG work argues that causal interventions help distinguish decisive evidence from correlated but misleading evidence. RDLLM-L26 turns that research direction into a deployable audit artifact by replaying source-removal interventions for each credited work.

Sources: Nematov et al., "Source Attribution in Retrieval-Augmented Generation" (2025); Dehghan and McDonald, "Who Benefits from RAG? The Role of Exposure, Utility and Attribution Bias" (2026); Qin et al., "Counterfactual Reasoning for Retrieval-Augmented Generation" (ICLR 2026); Liu et al., "Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation" (2026).

Multimodal RAG work makes the same problem harder: the evidence can be images, audio, video, tables, or mixed documents rather than plain text. Recent surveys and benchmarks such as Ask in Any Modality, MAVIS, and MiRAGE show that source support and citation quality need multimodal evaluation, not text-only citation checks. RDLLM-L27 turns that requirement into a deployable media report: registered media assets and submitted generation inputs are replay-matched through content hashes, perceptual-hash commitments, descriptor-hash commitments, ranked scores, owner payouts, and unattributed-media escrow.

Sources: Abootorabi et al., "Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation" (2025); Song, Park, and Kim, "MAVIS: A Benchmark for Multimodal Source Attribution in Long-form Visual Question Answering" (AAAI 2026); Martin et al., "Seeing Through the MiRAGE: Evaluating Multimodal Retrieval Augmented Generation" (2025).

Recent model-internal attribution work shows why public citations alone are not enough. Hidden-state probes can test whether generated text used retrieved context; mechanistic data attribution traces interpretable model units back to training samples; probabilistic attribution estimates prior-token influence from next-token probabilities; attribution-graph methods preserve causal structure through the generation; and the Attribution Contract argues that every attribution claim must state exactly what output, features, process, and score it explains. Attribution Bias in Large Language Models adds a practical user-facing failure mode: suppression, where a model has attribution information but omits visible credit. RDLLM therefore makes suppression a named verifier field in the answer provenance card and source-confidence taxonomy. RDLLM-L28 turns those findings into a deployable model-signal report: providers publish scalar log-probability, activation, gradient, attention, and memorization signals under an explicit attribution contract, commit to private telemetry, pay accepted owners, and escrow weak or zero-confidence influence without disclosing raw hidden states or logits.

Sources: Brink, Boer, and Ulmer, "Probing for Knowledge Attribution in Large Language Models" (2026); Chen, Luo, and Pan, "Mechanistic Data Attribution" (2026); Shilpika et al., "Probabilistic Attribution For Large Language Models" (2026); Berman et al., "Attribution Bias in Large Language Models" (2026); Walker and Ewetz, "Explaining the Reasoning of Large Language Models Using Attribution Graphs" (2025); Nguyen, "The Attribution Contract" (2026).

Provenance Standards

W3C PROV defines provenance as information about entities, activities, and people involved in producing a piece of data or thing, supporting assessments of quality, reliability, and trustworthiness. C2PA develops technical standards for certifying the source and history of media content. Royalty Driven LLM ledgers should align with these provenance concepts, even if the prototype uses simple JSON hashes. C2PA also clarified in 2026 that Content Credentials do not express TDM or AI-training preferences, so rights permissions need a separate policy layer rather than being collapsed into provenance metadata. Recent security work also cautions that content-provenance metadata is not enough by itself for high-stakes attribution. RDLLM therefore treats C2PA-style provenance as one ingredient, then adds private replay, independent verification, payout conservation, and escrow.

Sources: W3C PROV Overview (2013); C2PA Specifications (2026); C2PA TDM clarification (2026); Golaszewski et al., "Verifying Provenance of Digital Media: Why the C2PA Specifications Fall Short" (2026).

W3C Verifiable Credentials 2.0, published as a W3C Recommendation, provides a portable pattern for issuer/subject/proof based claims. RDLLM's ownership attestations are intentionally simple JSON today, but the registry design maps naturally to VC-style credentials: an issuer attests that a creator controls a work, binds evidence hashes and identifiers, and allows verifiers to reject or escrow claims when credentials conflict. The current prototype also maps attribution receipts and escrow settlement reports into VC-shaped credentials, while mapping answer provenance into a PROV-shaped entity/activity/agent graph. This makes attribution portable across providers, registries, wallets, audit systems, and transparency services.

Source: W3C Verifiable Credentials Data Model v2.0 (2025).

Rights Expression Standards

W3C ODRL provides a standard model for expressing permissions, prohibitions, duties, and constraints over content and services. This maps directly onto RDLLM license scope: training, retrieval, generation, display, quote, external attribution, jurisdiction, minimum royalty duties, and revocation. RDLLM's rights manifest uses ODRL-style structures while remaining simple JSON.

Source: W3C ODRL Information Model 2.2.

Transparency and Attestation Standards

The upgraded mechanism follows the same pattern that software supply-chain security uses for trust: emit a signed statement, register it in a transparency service, and allow independent verification by inclusion proof. IETF SCITT defines an architecture for trustworthy and transparent digital supply chains using signed statements, transparency services, and receipts. Sigstore Rekor demonstrates practical public transparency logs with artifact digests and inclusion proofs. The in-toto/SLSA attestation pattern shows how production metadata can be expressed as verifiable statements about an artifact.

Sources: IETF SCITT/RFC 9943; RFC 9162 Certificate Transparency; Sigstore Rekor documentation; in-toto/SLSA attestation specifications.

Conformance and Certification

C2PA's conformance program shows that provenance standards become more useful when vendors can submit evidence, validate generator and validator behavior, and appear on a conforming-products list. RDLLM follows that lesson with a local certification suite. The report is not a legal certification, but it is a portable technical artifact that proves whether an implementation passes grounded-generation, external-text attribution, escrow, rights-blocking, receipt/transparency, tamper-detection, and rights-manifest cases. The latest RDLLM suite adds an RDLLM-L7 level for grounding-quality certification: source availability, citation integrity, evidence relevance, fact support, policy alignment, and payout alignment must agree, and every paid non-escrow source must be visible in the source footer. It also adds RDLLM-L8 for registry-trust certification: duplicate ownership claims must be detected before settlement, disputed works must route to registry-dispute escrow, and the receipt must bind the registry report hash and conflict decisions to the event. The next level, RDLLM-L9, proves settlement finality: when a dispute is resolved, escrow release happens through a separate report that binds the original event hash, registry conflict, resolution evidence, payout split, balances, report hash, and signature rather than rewriting the historical receipt. RDLLM-L10 proves interoperability: attribution receipts, PROV-shaped answer graphs, and optional escrow-settlement credentials must verify their hashes and deterministic proofs, and must fail when their receipt or settlement bindings are tampered with. RDLLM-L11 proves attribution-gap accountability: every source accessed by retrieval or text matching must be user-visible, paid, or explicitly withheld through rights-conflict or registry-dispute escrow. The suite also proves that hiding a paid source from the footer opens a verifiable gap. RDLLM-L12 proves selective-disclosure accountability: public receipts can expose source attribution and claim-support metadata while salted commitments bind private source quotes, claim evidence text, access traces, economics, rights decisions, and registry decision internals. The suite proves that public receipt drift and disclosed-leaf tampering are rejected. RDLLM-L13 proves trace-exchange accountability: OpenTelemetry-aligned generation, source-access, citation, and claim-support spans must match the signed receipt and ledger. The suite proves that omitted provider source-access spans and relabeled citation hashes are rejected. RDLLM-L14 proves aggregate royalty-statement accountability: many private usage events roll up into creator, escrow, work, source-usage, receipt, and trace commitments. The suite proves payout conservation, private-text redaction, receipt/trace root binding, and rejection of creator-statement drift. RDLLM-L15 proves creator challenge correction: an omitted source can be accepted for corrective payment without rewriting the original event, already credited sources receive no double payment, private text remains hidden, and remedy tampering is rejected. RDLLM-L16 proves provider-card accountability: a provider can publish a signed, privacy-preserving attribution posture card that binds certification evidence, ledger coverage, supported evidence channels, public disclosure surfaces, challenge policy, limitations, and evidence roots. The suite rejects stale certification evidence and coverage tampering. RDLLM-L17 proves training-summary accountability: a provider can publish a GPAI/Croissant/SPDX/ODRL-aligned training-content summary that binds corpus categories, rights coverage, license/use counts, policy roots, content-hash roots, and training-value commitments while redacting private work text. The suite rejects stale certification/provider-card evidence and coverage tampering. RDLLM-L18 proves public assurance-bundle accountability: providers publish hash-only proof-pack entries, Merkle roots, inclusion proofs, and profile flags aligned with SCITT/Rekor/in-toto/C2PA-style verification patterns. The suite rejects artifact-hash tampering, missing inclusion proofs, invalid signatures, and private payload disclosure. RDLLM-L19 proves answer-provenance-card accountability: visible source footers and claim span hashes are bound to receipt hashes, trace hashes, grounding verdicts, and attribution-gap verdicts without revealing private prompt, answer, claim, source quote, or evidence text. The suite rejects footer relabeling and card tampering. RDLLM-L20 proves source-materialization accountability: cited source hashes, quote hashes, source URIs, claim evidence spans, answer-card bindings, and visible footer prefixes resolve to registered content without revealing prompt, answer, source, quote, claim, or evidence text. The suite rejects fabricated source hashes, stale answer-card bindings, and claim evidence that cannot be reproduced from the registered corpus. RDLLM-L21 proves response-envelope accountability: rendered answers, answer cards, source verification reports, provider cards, certification posture, and public receipts are packaged into one signed API artifact that can be verified without the private ledger or source corpus. The suite rejects rendered-output tampering and embedded-artifact tampering. RDLLM-L22 proves integration-profile accountability: providers publish a signed API contract with generation and verification endpoints, required headers, embedded artifact requirements, verifier commands, schemas, public surfaces, readiness checks, and bound proof hashes. The suite rejects profile tampering, provider-surface drift, certification regression, and response-envelope drift. RDLLM-L23 proves discovery-manifest accountability: providers publish a signed /.well-known/rdllm.json entry point that catalogs the provider card, certification report, integration profile, response envelope, assurance bundle, optional training summary, API contract hash, schemas, verifier commands, readiness checks, and bound proof hashes. The suite rejects discovery path tampering, certification regression, provider-surface drift, artifact hash drift, and assurance bundles that omit integration-profile or response-envelope evidence. RDLLM-L24 proves derivative-lineage accountability: summaries, curated datasets, synthetic examples, tool outputs, and transformed corpora can carry machine-readable upstream work edges, and settlement obligations split derivative source payouts between immediate and upstream owners while conserving the source payout. The suite rejects missing upstream works, lineage cycles, declared upstream hash drift, payout drift, private-text leakage, and report tampering.

RDLLM-L25 proves benchmarked provenance accountability: providers publish a signed rdllm-provenance-evaluation/v1 report that replays clean-source, paraphrase, hard-decoy, unattributed-escrow, and derivative-lineage cases. The suite rejects report tampering, omitted cases, source-ranking drift, signature drift, and disclosure of raw benchmark prompts, answers, or source text.

RDLLM-L26 proves counterfactual influence accountability: providers publish a signed rdllm-counterfactual-influence/v1 report that removes each credited work, replays the same prompt and answer, and records whether the source disappeared, payout reallocated or escrowed, and the credited work had a decisive marginal influence score. The suite rejects report tampering, ablation drift, signature drift, and disclosure of raw prompt, answer, source, quote, or claim evidence text. The public proof pack includes a decisive-source counterfactual vector so the artifact demonstrates a positive influence margin, not only replaceable-source accounting.

RDLLM-L27 proves multimodal media attribution: providers publish a signed rdllm-media-attribution/v1 report that matches image, audio, video, 3D, and text-shaped media signatures to registered assets, pays matched owners, escrows weak or unknown media influence, and rejects raw media or descriptor disclosure.

RDLLM-L28 proves model-internal signal attribution: providers publish a signed rdllm-model-signal-attribution/v1 report that explains which output is being attributed, which features are eligible for credit, which score is attributed, and what is held fixed. The report verifies private log-probability, activation, gradient, attention, and memorization telemetry through commitments, pays accepted owners, escrows weak or zero-confidence influence, and rejects raw hidden state, token-logit, prompt, output, or chain-of-thought leakage.

RDLLM-L29 adds post-publication rights remediation: providers publish a signed rdllm-rights-remediation/v1 report comparing previous and updated rights states, including revocation, opt-out, license, allowed-use, prohibited-use, jurisdiction, and minimum-royalty changes. The report preserves historical event IDs and event hashes instead of rewriting past usage, then runs future-use probes across training, retrieval, generation, external attribution, display, and quote. Revoked or newly prohibited use must be denied, retrieval must stop surfacing the changed work, and blocked text-output probes must route the creator pool to rights_conflict_escrow. The public artifact discloses policy hashes, content hashes, event hashes, reasons, and escrow summaries, but not work text, prompts, outputs, matched text, or private ledger payloads.

RDLLM-L30 adds semantic text attribution: providers publish a signed rdllm-semantic-text-attribution/v1 report that attributes paraphrased, summarized, or externally generated text to registered source owners using replayable lexical, concept, distinctiveness, span, and decoy margin scores. Accepted owners receive the creator-pool share and public footer rows; ambiguous, unmatched, or policy-blocked text routes to semantic or rights-conflict escrow. The public artifact discloses source IDs, source URIs, hashes, scores, footer commitments, and payout shares, but not prompt text, output text, matched text, or source text.

RDLLM-L31 adds cross-provider attribution exchange: providers publish a signed rdllm-attribution-exchange/v1 manifest that imports provider-card, certification, integration-profile, discovery-manifest, response-envelope, assurance-bundle, and semantic-text reports by declared hash and payload hash. The exchange preserves public source-footer rows and escrow relay rules so another AI provider, search product, marketplace, or auditor can verify and forward upstream attribution obligations without seeing private prompt, answer, matched, or source text.

RDLLM-L32 adds portable conformance vectors: providers publish a signed rdllm-conformance-vector-pack/v1 artifact that binds fixtures, expected public outcomes, verifier commands, and negative mutations. This is the standards-body layer: an external foundation-model provider can implement against the vector pack and prove that response envelopes, discovery, semantic attribution, exchange relay, full-stack certification, and privacy commitments fail predictably when hashes, footers, certification levels, or expected outcomes drift.

RDLLM-L33 adds runtime federation handshakes: providers publish and verify a signed rdllm-federation-handshake/v1 artifact before a downstream AI system consumes an upstream answer, proof pack, or generated work. The handshake binds the requester identity, provider identity, requested minimum level, negotiated level, provider-card hash, certification hash, integration profile hash, discovery hash, response-envelope hash, semantic-text report hash, attribution-exchange hash, conformance-vector hash, required runtime headers, source-footer relay obligations, escrow relay obligations, and downgrade rejection. This closes the gap between static publication and live provider-to-provider use: an API caller can reject missing vectors, missing exchange manifests, stale hashes, unsigned material changes, or private-text leakage before relying on the answer.

RDLLM-L34 adds portable attribution capsules: providers publish and verify a signed rdllm-attribution-capsule/v1 artifact for copied, reposted, exported, or metadata-wrapped AI outputs. The capsule binds the rendered-output hash, response-envelope hash, federation-handshake hash, attribution-exchange hash, conformance-vector hash, provider-card hash, certification hash, discovery hash, copyable footer marker, delivered-body hash, runtime capsule headers, C2PA-compatible assertion pointer, and SCITT-like statement subject. This closes the user-facing attribution gap identified by recent LLM-search studies: the source footer and royalty proof can remain verifiable after content leaves the original chat/API surface, and copied-body tampering is detected when the marker survives but the answer text changes, while prompts, answers, matched text, source text, hidden states, and private ledger payloads remain outside the public capsule.

RDLLM-L35 adds an emit-time response release gate: providers publish and verify a signed rdllm-response-release-gate/v1 artifact before an answer is shown. The gate binds the response envelope, answer provenance card, source materialization report, attribution capsule, provider attribution card, and certification report, and emits decision: emit only when source labels, claim span prefixes, source materialization, capsule delivery contract, public provider surface, and minimum upstream certification all verify. This directly addresses the recent citation-verification finding that working links and plausible source labels do not guarantee factual support: unsupported or unverifiable answers are held before display instead of being released with decorative footers.

RDLLM-L36 adds proof-carrying responses: providers publish and verify a signed rdllm-proof-carrying-response/v1 delivery object at the model API boundary. The object contains the public answer only when the release gate verifies; otherwise it returns a held-response notice and suppresses the original answer. This follows the proof-carrying-data pattern from software supply-chain and transparency-log systems: the consumer receives the artifact and the verification evidence together, and any displayed answer can be checked against its release gate, response envelope, attribution capsule, provider card, and certification report.

RDLLM-L37 adds serving gateway reports: providers publish and verify a signed rdllm-serving-gateway-report/v1 artifact for the API route that served the answer. The gateway report hash-commits the private prompt and raw model output, embeds the proof-carrying response, binds the release-gate and proof-response hashes, and proves the delivered-output hash equals the proof-carrying response copied output. This makes adoption testable at the production egress boundary: a provider cannot merely publish proof artifacts offline while routing unverified answers around them.

RDLLM-L38 adds creator license contracts: providers publish and verify a signed rdllm-creator-license-contract/v1 artifact that binds registered works to allowed AI uses, attribution duties, compensation duties, minimum creator-pool terms, revocation state, content hashes, and hashed payout-account commitments before use. This connects user-facing source footers to the rights layer: a cited source is not only materialized and grounded, but also covered by a machine-readable use contract or routed through the existing escrow path.

RDLLM-L39 adds source confidence reports: providers publish and verify a signed rdllm-source-confidence-report/v1 artifact that joins the answer provenance card, source materialization report, and creator license contract into public footer rows labeled verified, warning, or failed. It also publishes a hallucination taxonomy for fabricated sources, metadata drift, hash mismatches, footer omissions, attribution suppression, license gaps, unsupported claims, and evidence-span gaps. This is the user-trust layer: a footer is treated as grounded only when source identity, evidence continuity, license terms, and claim support all verify.

RDLLM-L40 adds citation footer contracts: providers publish and verify a signed rdllm-citation-footer-contract/v1 artifact that binds the exact client-renderable source rows, claim anchors, confidence labels, license status, royalty status, display order, row hashes, and footer hash to the response envelope. This moves source attribution from "the model wrote a footer" to "the client can only render a footer that matches public materialization, license, confidence, and response-boundary proofs."

RDLLM-L41 adds private audit challenges: providers publish and verify a signed rdllm-private-audit-challenge/v1 artifact that binds an auditor nonce to selected redacted receipt paths, value hashes, salt hashes, leaf hashes, and opening commitments. This lets authorized auditors test hidden source-access, claim-evidence, rights, registry, and royalty facts without publishing private prompts, evidence text, salts, or payout accounts.

RDLLM-L42 adds transitive attribution reports: providers publish and verify a signed rdllm-transitive-attribution-report/v1 artifact whenever a copied RDLLM output becomes downstream input. The report binds the downstream event hash and copied-input hash to the upstream attribution capsule and response envelope, verifies that the copied marker is present and the copied body hashes to the upstream subject, carries answer-card source rows forward, and splits a configured pass-through share of the downstream creator pool across the original source owners. This closes the attribution-laundering gap: a downstream model, platform, marketplace, or agent can add local credit, but it cannot erase the upstream rows or settle the reused answer as if the source trail ended at the wrapper.

RDLLM-L43 adds cross-provider clearinghouse reports: providers, collectives, marketplaces, and auditors can publish and verify a signed rdllm-clearinghouse-report/v1 artifact that ingests royalty statements and transitive attribution reports, normalizes their obligations into payable, escrow, and held rows, and holds duplicate or overlapping submissions instead of paying them twice. This turns per-response and per-provider attribution proof into a settlement layer that can operate across many model vendors.

RDLLM-L44 adds verifiable remittance reports: providers and creator collectives can publish rdllm-remittance-report/v1 artifacts that convert cleared payable and escrow rows into instruction-only payment rows with payout-account hashes, end-to-end IDs, remittance references, and preserved holds. This proves payment intent and reconciliation without publishing bank details or claiming funds moved before a payment processor executes the file.

RDLLM-L45 adds third-party audit attestations: providers, auditors, creator collectives, marketplaces, and enterprise buyers can publish and verify rdllm-third-party-audit-attestation/v1 artifacts over the public proof pack. The attestation binds the provider card, certification report, certification attestation, integration profile, discovery manifest, stable assurance bundle, response envelope, source-confidence report, citation-footer contract, clearinghouse report, remittance report, revenue allocation report, and finance ledger attestation by hash, replays the public verifier path where inputs are available, and proves the audit was not merely provider self-attestation. Settlement reports remain outside the stable assurance bundle and are bound at the audit layer to avoid cyclic proof dependencies. This maps source attribution into the assurance pattern already used by SCITT, in-toto, Rekor-like logs, and C2PA conformance, while keeping private prompts, answer text, source text, evidence text, and payout accounts out of the public artifact.

RDLLM-L46 adds usage revenue allocation reports: providers can publish and verify rdllm-revenue-allocation-report/v1 artifacts that turn hashed billing, advertising, subscription, API, enterprise, or marketplace revenue pools into per-event gross revenue before creator-pool payout calculation. This closes the remaining financial-trust gap: a creator can inspect whether a payable event's gross revenue was allocated from conserved source pools, whether receipt hashes bind the same event, and whether creator-pool totals match the event economics without exposing raw customer accounts, invoice text, or bank details.

RDLLM-L47 adds finance ledger attestations: providers, auditors, creator collectives, marketplaces, and enterprise buyers can publish and verify rdllm-finance-ledger-attestation/v1 artifacts that reconcile hash-only finance exports to the revenue-source pools used by the allocation report. The attestation does not publish customer records, invoices, payment methods, prompts, outputs, or source text. Instead, it binds each private finance row to an external record hash, rolls those rows up by revenue source, proves the rollups match the revenue allocation report, and rejects duplicate rows, missing source mappings, currency drift, amount drift, stale hashes, and private-field leakage. This closes the last pre-settlement trust gap: creators can verify not only that a usage event received allocated gross revenue, but that the allocation pool was itself tied to external billing, invoice, ad-server, API-meter, enterprise-contract, marketplace-order, or other finance-system evidence.

RDLLM-L48 adds proof dependency graphs: providers can publish and verify rdllm-proof-dependency-graph/v1 artifacts that turn the proof pack into a replayable DAG. Each graph names artifacts by hash, separates hard verifier prerequisites from publication commitments such as Merkle bundle inclusion, emits a deterministic topological replay order, and rejects cycles, unknown dependencies, stale graph hashes, non-reproducible artifact hashes, and private-field leakage. This gives auditors and downstream model providers a portable replay plan instead of forcing them to infer artifact ordering from prose.

RDLLM-L49 adds publication monitors: providers can publish and verify rdllm-publication-monitor/v1 artifacts that checkpoint required public proof surfaces over time. Each monitor binds artifact hashes into a Merkle snapshot, records an append-only checkpoint chain, reports diff metadata, and blocks certification regression or required-artifact removal. This adapts transparency-log practice to attribution evidence: the question is not only whether an answer had a source footer once, but whether the public proof surfaces behind that footer remain reproducible and non-regressed after release.

RDLLM-L50 adds publication witnesses: providers can publish and verify rdllm-publication-witness/v1 artifacts that bind publication-monitor checkpoints to independent witness attestations. The report enforces a quorum policy, detects split views across monitor issuers and checkpoint indexes, and exposes only checkpoint hashes and metadata. This adapts transparency-log witness practice to attribution: users and auditors can reject a source footer or royalty proof if the provider cannot show that the underlying public proof history was seen consistently by independent witnesses.

RDLLM-L51 adds trust registries: providers can publish and verify rdllm-trust-registry/v1 artifacts that bind active provider, auditor, and witness signing keys to public proof artifacts, key rotations, revocations, and witness attestations. The public report uses key IDs, key hashes, artifact hashes, and signature-verification status rather than raw key material. This closes the trust-root gap left by witnessed publication: a source footer is not only grounded and witnessed, but also tied to non-revoked signer and witness keys that independent verifiers can replay.

RDLLM-L52 adds certification attestations: providers or independent certifiers can publish and verify rdllm-certification-attestation/v1 artifacts that sign the certification report hash, attested level, level root, case-status root, certifier identity, target provider, and validity metadata. This closes the remaining certification gap: a source footer is not merely backed by a provider-hosted certification report, but by a separately signed attestation that can be included in a trust registry and replayed without exposing prompt text, source text, claim evidence, or case payloads.

RDLLM-L53 adds generated-code attribution: providers can publish and verify rdllm-code-attribution-report/v1 artifacts that rank generated code against registered source snippets, bind exact line hashes and token/identifier commitments, check SPDX-style license compatibility, pay compatible owners, and escrow strong copied-code signals when license or policy terms are incompatible. This extends attribution from prose and media into code assistants without exposing generated code, source code, or matched private text.

RDLLM-L54 adds pre-settlement claim verification: providers can publish and verify rdllm-claim-verification-report/v1 artifacts that require trusted signed ownership attestations before direct settlement and route weak, unverified, or duplicate ownership claims to escrow/review. This closes the incentive-abuse gap: attribution evidence can identify a source, but the payout path still needs independent ownership evidence before money leaves escrow.

RDLLM-L55 adds source availability verification: providers can publish and verify rdllm-source-availability-report/v1 artifacts that bind each user-facing citation footer row to a reachable or archived source snapshot, registered content hash, source-materialization report, citation-footer contract, and cited claim-span hashes. This closes the inspectability gap: a footer can be cryptographically bound and still be useless to a user if the referenced material is stale, unreachable, or not the material that supported the answer.

RDLLM-L56 adds evidence sufficiency verification: providers can publish and verify rdllm-evidence-sufficiency-report/v1 artifacts that rank candidate evidence spans for every generated claim, require the cited span to be the top-ranked minimal sufficient support, require an explicit margin over decoy evidence, and bind the result to the source-availability report, source-materialization report, and citation-footer contract. This closes the overcitation and weak-citation gap: a source can exist and be reachable while the specific visible claim still points users to redundant, ambiguous, or non-best evidence.

RDLLM-L57 adds counterevidence adjudication: providers can publish and verify rdllm-counterevidence-adjudication-report/v1 artifacts that scan registered source spans for contradiction candidates, require unaddressed counterevidence to be zero before release, and bind the decision to source availability, source materialization, evidence sufficiency, and citation-footer contracts. This closes the single-sided grounding gap: a claim can have a good cited support span while other registered material directly disputes it.

RDLLM-L58 adds release grounding closure: providers that claim L55-L57 certification must embed and bind source availability, evidence sufficiency, and counterevidence reports inside the public response envelope before the release gate can emit the answer. This closes the certification/application gap: a provider cannot publish late-stage grounding artifacts as side files while serving a response envelope that did not actually depend on them.

RDLLM-L59 adds answer claim coverage: providers that claim L59 must publish rdllm-answer-claim-coverage-report/v1 artifacts that replay the public answer surface into support-bearing sentence hashes. Every such sentence must match a verified, sufficient, counterevidence-free claim row. The extractor skips structured source and claim footer rows, but it does not trust footer position; an unsupported sentence appended after the footer is treated as public answer text and fails release.

RDLLM-L60 adds generation context closure: providers that claim L60 must publish rdllm-generation-context-closure-report/v1 artifacts that replay each verified, displayed claim to source-access spans and redacted context block commitments captured before generation. This blocks post-hoc attribution: a source footer is not enough unless the cited evidence was already available in the model's traced generation context.

RDLLM-L61 adds source boundary integrity: providers that claim L61 must publish rdllm-source-boundary-report/v1 artifacts that replay each generation-context source packet against trace telemetry proving that the packet was role-labeled as evidence, excluded from control and instruction channels, content-hash bound, and unable to modify attribution or payout policy. This blocks a different failure mode from post-hoc citations: retrieved content may be factually relevant while also carrying malicious or self-serving instructions.

RDLLM-L62 adds decision provenance: providers that claim L62 must publish rdllm-decision-provenance-report/v1 artifacts after the response release gate. The report builds a hash-only influence graph over claim-grounding decisions, visible footer decisions, royalty participation decisions, and the release decision. Verifiers reject missing proof edges, unknown artifact nodes, private prompt/source text, payout decisions influenced directly by retrieved source text, and release decisions that are not bound to response-envelope, release-gate, trace-exchange, attribution-capsule, and source-boundary proofs. This makes the footer not just visible but accountable: users can see which proof channel justified each cited source, and auditors can separate evidence use from control, policy, and payout influence.

RDLLM-L63 adds calibrated attribution confidence: providers that claim L63 must publish rdllm-calibrated-attribution-confidence/v1 artifacts after decision provenance. The report binds each visible claim, source-footer row, and payout-participation row to benchmark-backed lower confidence bounds derived from the provider's portable provenance-evaluation results. Verifiers reject benchmark drift, missing decision-provenance edges, private prompt/source text, and undisclosed low-confidence rows. This directly addresses the current research warning that attribution and faithfulness scores are easy to overread unless they expose calibration, uncertainty, and benchmark suitability.

RDLLM-L70 through RDLLM-L186 add settlement-grade replay, copy-survival gates, payment execution proof, payment-rail authenticity, creator-facing payout receipts, rendered attribution audits, training-memory provenance, evidence-locked generation, emission enforcement, live witness quorum, live witness transparency inclusion, attested attribution runtime binding, claim-source attribution footers, causal evidence-utility attribution, parametric memory attribution, style influence attribution, model-lineage attribution, black-box model provenance, dispute adjudication, post-adjudication settlement adjustment, residual corpus royalty settlement, valuation-method audit, evidence-region binding, source access leasing, content-protocol ingestion, citation-reliance receipts, license-transaction receipts, grounded source footer receipts, source footer delivery receipts, foundation API attribution profiles, client attribution enforcement receipts, persistent memory provenance receipts, private reasoning attribution receipts, post-training signal provenance receipts, attribution bills of materials, creator attribution audit indexes, creator attribution audit federations, creator audit federation transparency, creator audit transparency monitoring, creator audit private watch receipts, deep-research citation audits, source freshness audits, royalty-abuse settlement gates, consent revocation propagation gates, evidence-force calibration, warranted source footers, universal citation verification, universal grounded reuse, universal training-to-serving attribution contracts, universal confidential attribution audits, universal attribution authority control planes, universal RDLLM roots, universal emission enforcement gateways, universal composite RDLLM profiles, universal runtime conformance receipts, universal claim provenance envelopes, and universal provider wire protocols, universal accountability audit trails, universal accountability witness quorums, universal grounded reliance contracts, universal reliance correction ledgers, universal foundation adoption kernels, and universal provider adapter harnesses, universal provider drift sentinels, universal attribution negotiation handshakes, universal negotiated invocation enforcement, universal certification trust federation, universal foundation provider adoption packs, universal industry adoption roots, and universal reference implementation distributions, universal live attribution proofs, universal foundation-model release passports, universal composite RDLLM contracts, universal foundation provider binding matrices, universal production invocation admissions, universal source-grounded response receipts, universal distribution reliance passports, universal adversarial provenance quorums, and universal procurement/regulatory reliance contracts. RDLLM-L185 adds universal provider meter normalization: provider-native usage, cache, reasoning, tool/search, media, batch, invoice, router, pricing, and quota meters must normalize into privacy-safe RDLLM settlement meters before invocation, response release, footer reliance, or creator settlement. RDLLM-L186 adds universal provider response-state normalization: provider-native finish, stop, refusal, safety, guardrail, truncation, tool, stream-final, and error states must normalize into a privacy-safe RDLLM response state before a displayed answer can claim source-footer reliance or release creator settlement. Blocked, filtered, truncated, tool-only, errored, or unknown terminal states fail closed so a footer cannot make an unsupported or incomplete answer look grounded. L165 closes the decorative-citation gap: each response must publish a live attribution proof binding visible footer sources to identity verification, claim support, evidence utility, factual confidence, knowledge-source classification, attribution-suppression checks, and settlement participation. This prevents a provider from pairing a correct answer with a wrong, merely decorative, hidden, or low-confidence source while still implying grounded attribution. L166 closes the model-release claim gap: a named model/version must carry a foundation-model release passport before a provider can claim RDLLM compliance, invoke that model through supported provider routes, rely on source footers, or release direct creator settlement. The passport binds model identity, training summary, copyright/TDM policy, post-training lineage, route adapters, live attribution, revocation status, and settlement meters, and it fails closed for unsupported routes, revoked releases, missing live attribution, or settlement without the model passport. L167 closes the fragmented-reliance gap: a deployment must publish one universal composite RDLLM contract before any universal RDLLM claim, foundation-model invocation claim, response-release claim, source-footer reliance, procurement reliance, or creator settlement release can be accepted. The contract binds the model-release passport, live attribution proof, post-release proof graph, public discovery surfaces, canonical API gates, settlement evidence, revocation status, standard mappings, and negative fixtures into one signed verifier decision. This prevents a provider from citing isolated proofs while leaving the actual model route, footer renderer, customer API, copied-output status, or settlement meter outside the audited mechanism. L168 closes the named-provider binding gap: the L167 composite contract must be mapped to each provider family's actual native API, streaming format, tool-call surface, citation/grounding representation, telemetry, revocation check, copy/export status, auditor export, and settlement meter before a route can claim universal RDLLM adoption. This responds to the current evidence that model documentation remains fragmented across providers and that link-level citation presence does not prove source relevance, factual support, or claim-evidence alignment. L168 therefore treats provider API adapters as auditable obligations: OpenAI-compatible, Anthropic, Google, Meta/Llama, Mistral, Cohere, xAI, DeepSeek, cloud gateway, router, local runtime, RAG, and MCP/agent routes must all fail closed when aliases drift, SDK shapes change, streams drop footer bindings, tool calls lose source context, gateways rewrite responses, local runtimes lack attestation, fallback models lack passports, telemetry meters diverge, or private payloads leak. L169 closes the executable-provider evidence gap: the L168 provider binding matrix is no longer enough by itself. Each named provider family must publish a signed conformance runner receipt proving that official fixture suites were freshly replayed against native sync, streaming, tool-call, retrieval/grounding, response-envelope, source-footer, live-attribution, telemetry, settlement, revocation, copy/export, auditor-export, and negative-canary surfaces. The receipt binds runner-image verification, provider identity, native transcripts, public result hashes, and fail-closed negative canaries before provider onboarding, source-footer reliance, procurement reliance, or creator settlement is allowed for that route. L170 closes the live-invocation admission gap: a provider route that passed L169 still must prove that the specific production call was admitted before it was sent, streamed, rendered, copied, exported, used for tool/MCP execution, or settled. Each admission binds the current L169 receipt, provider family, route, model alias, tenant scope, negotiated invocation guard, drift sentinel, telemetry span, retrieval/source gate, source-footer release gate, revocation snapshot, and settlement meter. Negative fixtures fail closed for missing or stale receipts, provider mismatches, route drift, missing spans, missing footer gates, unbound settlement meters, stale revocation, unadmitted stream chunks, unscoped tool calls, unadmitted cache reuse, and private payload leaks. L171 closes the final-answer grounding gap: an admitted provider call still does not prove that the answer shown to the user contains the correct source footer or that settlement is tied to the visible supported sources. Each source-grounded response receipt binds L170 admission and L165 live attribution to source category rows, claim-grounding rows, response-surface rows, citation metadata, copy/export preservation, and settlement-release rows. Negative fixtures fail closed for missing footers, unsupported claims, fabricated sources, unavailable or mismatched citations, right-answer/wrong-source cases, hidden payable sources, unsupported parametric claims, low-confidence releases, post-hoc footers, stripped copy exports, settlement without a grounded footer, and private payload leaks. L172 closes the post-answer distribution gap: a grounded answer can still lose its source footer, locator, status resolver, content credential, reuse meter, or settlement obligation after copy, export, embedding, API relay, screenshot, or downstream RAG ingestion. Each distribution reliance passport binds the L171 receipt and L136 content credential to clipboard, Markdown, HTML, PDF, screenshots, content credentials, API relays, web embeds, email/social shares, downstream RAG ingestion, and marketplace dataset exports. It also binds portable status channels for locators, citation URL health, revocation, correction, settlement status, and independent audit export. Negative fixtures fail closed for stripped footers, removed locators, missing credentials, unreachable resolvers, stale revocation snapshots, unmetered downstream reuse, dropped settlement obligations, export surfaces without attribution, and private payload leaks. L173 closes the adversarial provenance gap: a distributed answer can carry a plausible-looking footer or content credential while an attacker substitutes the manifest, replays an old signature, spoofs footer text, phishes locators, creates resolver split views, strips PDF metadata, crops screenshots, rewrites API relays, poisons downstream RAG context, impersonates creator IDs, or forks settlement meters. The universal adversarial provenance quorum requires independent visible, machine-readable, credential, witness, transparency, resolver, locator, body-hash, perceptual, watermark/marker, settlement-meter, and creator-audit signals to agree under negative fixtures before high-stakes reliance or settlement release is allowed. L174 closes the procurement and regulator reliance gap: a provider can publish technical attribution proofs while its terms, marketplace listing, enterprise contract, router, regulator export, or settlement workflow leaves source-footer duties and creator remedies unenforceable. The universal procurement/regulatory reliance contract binds conformance claims, model versions, footer duties, machine-readable source duties, distribution survival, adversarial quorum checks, audit rights, regulator exports, creator challenge routes, settlement holds, correction SLAs, procurement SLAs, marketplace delisting, jurisdiction mappings, and negative procurement fixtures to the L173 quorum before any provider claim, marketplace listing, procurement decision, regulator reliance, or creator settlement release is allowed. L175 closes the provider onboarding and migration gap: a provider can sign an L174 reliance contract while old endpoints, SDK shims, gateway proxies, model aliases, streaming finals, tool outputs, batch responses, regulator exports, or rollback routes still strip source footers or bypass attribution enforcement. The universal provider onboarding/migration covenant binds provider-family rows, native API surface rows, migration artifacts, rollout gates, rollback controls, and negative onboarding fixtures to the L174 contract, L168 binding matrix, and L169 conformance runner before native provider support, customer migration, marketplace rollout, regulator rollout, or settlement release is allowed. L176 closes the dynamic model-route gap: provider onboarding does not prove that new aliases, hosted open-weight services, local runtimes, regional catalogs, private deployments, marketplace routes, or router fallbacks are registered. The universal model/provider registry binds every declared route to catalog sources, provider namespaces, adapter manifests, lifecycle events, source-footer support, machine-readable source metadata, and settlement meters before any route can claim RDLLM support. L177 closes the user-facing source-footer enforcement gap: source payment and internal attribution do not substitute for visible source grounding. The universal source-footer enforcement contract binds every L176 route to source discovery, retrieval trace capture, claim decomposition, evidence-span binding, source identity resolution, citation metadata verification, counterevidence scanning, no-source abstention, visible and machine-readable footer rows, copy/export preservation, and settlement holds before final answer release. L178 closes the provider catalog coverage gap: a registered route list is not enough unless every live catalog entry from provider endpoints, cloud catalogs, marketplaces, gateways, hosted open-weight registries, private deployments, local runtimes, regional catalogs, SDK metadata, billing meters, and lifecycle feeds is exhaustively normalized. The universal provider catalog coverage contract requires each discovered model to be admitted into an L176 route with L177 source-footer enforcement or explicitly blocked, with unknown models, stale snapshots, partial catalogs, unresolved aliases, capability mismatches, missing meters, and private payloads failing closed. L179 closes the live runtime binding gap: a catalog-covered route can still be bypassed if the actual request, provider response metadata, stream final event, tool callback, batch callback, cache reuse, telemetry span, source footer, or settlement meter refers to a different model alias or fallback. The universal runtime route binding contract binds runtime request and response model IDs, route IDs, alias resolution, fallbacks, telemetry, footers, and settlement meters to L178 catalog-covered routes before answer release or creator settlement. L180 closes the source-footer reliance gap: a visible citation row can look credible while the source is unavailable, metadata-drifted, irrelevant, factually unsupported, copied without its footer, or credited despite not being the work that supported the claim. The verified source-footer contract binds each rendered footer row to L179 live-route evidence plus L141 citation verification, L171 source-grounded response receipts, and L177 footer enforcement before response release, user reliance, copy/export, or settlement. L181 closes the model-capability coverage gap: a provider can have registered routes, catalog admission, runtime route binding, and verified source footers while an individual capability such as tool use, web search, image generation, audio, realtime sessions, embeddings, reranking, fine-tuning, batch jobs, or local inference remains untested. The universal model capability coverage contract requires each declared capability, modality pair, operation surface, and catalog-covered route to have a positive fixture, source-footer-or-abstention binding, settlement-meter binding, and negative fail-closed fixture before model invocation, response release, source-footer reliance, or creator settlement. L182 closes the live provider-capability evidence gap: a source footer is not fully grounded if the provider route claims an undocumented, stale, deprecated, region-incompatible, or endpoint-incompatible capability. The universal live capability discovery contract binds each declared capability to fresh official or attested provider sources, endpoint matrices, lifecycle status, region or tenant scope, and L181 route rows before invocation, response release, footer reliance, or creator settlement. L183 closes the provider-native annotation normalization gap: a model can emit URL citations, file citations, document citations, grounding metadata, streaming citation deltas, router-forwarded annotations, RAG retrieved contexts, local source maps, or generated-media source metadata in provider-specific formats that never reach the visible RDLLM footer. The universal native source annotation contract binds each native annotation format to parser fixtures, normalized footer fields, route annotation rows, verified footer row hashes, and negative fixtures before response release, footer reliance, or creator settlement. L184 closes the misleading-citation gap: a footer row can point to a real, accessible source while still being unsuitable for the question, misaligned with the user's intent, or unfaithful to the generated claim. The universal claim-evidence footer verification contract binds every displayed source row to structured citation parsing, materialized cited content, claim hashes, evidence spans, intent-purpose alignment, source-suitability scoring, answer-source fidelity, and factual-support verdicts before response release, footer reliance, or creator settlement. L157 specifically closes the provider-native fixture gap: every supported foundation provider and gateway must replay sync, streaming, tool, retrieval, batch, webhook, and copied-output fixtures into the same claim-provenance, source-footer, status-link, telemetry, and settlement-meter contract before the route can be treated as grounded or royalty-bearing. L158 closes the drift gap: provider API schemas, SDK response shapes, model aliases, streaming events, gateway transforms, citation locators, source-footer rendering, and settlement meters must be replayed through pre-release, hourly, daily, weekly, and incident-triggered canaries; stale routes revoke grounded display and hold creator settlement until remediation is published. L159 closes the request-time negotiation gap: a client and provider route must agree on the exact attribution contract, source footer, citation locator, claim-provenance envelope, model alias resolution, drift sentinel, telemetry, copy/export policy, privacy redaction, and settlement meter before model invocation; unnegotiated requests fail before generation rather than becoming post-hoc citation claims. L160 closes the runtime bypass gap: every direct API call, stream, SDK retry, gateway proxy, agent step, tool call, MCP tool call, retrieval context, batch callback, fallback route, and semantic-cache reuse must bind an invocation receipt to the L159 negotiated contract before response display, source-footer trust, copied-output reliance, or creator settlement release. Negative bypass fixtures must prove missing receipts, stripped negotiation headers, premature streaming chunks, tool/MCP schema substitution, unlocated retrieval context, unnegotiated fallback models, stale cache reuse, and settlement release without receipts are blocked, revoked, and settlement-held. L161 closes the untrusted-conformance gap: source-footer, citation, invocation, and creator-settlement claims must be certified through trust anchors, accredited certification authorities, conformance labs, trust marks, verifiable credentials, transparency inclusion, revocation status, and relying-party policy. Negative federation fixtures must prove self-signed claims, expired trust marks, revoked credentials, wrong provider subjects, stale certification hashes, missing transparency inclusion, split-view trust anchors, overbroad scopes, unaccredited labs, and private payload leaks block reliance and hold settlement. L162 closes the provider-adoption gap: the L161 trust chain must be packaged with provider-family adapter coverage, standard exports, fail-closed runtime gates, source-footer delivery, telemetry export, creator settlement guards, and negative adoption fixtures before any hosted API, cloud gateway, OpenAI-compatible router, local open-weight runtime, or enterprise proxy can claim grounded answers or release creator settlement. L163 closes the industry-root gap: the verified L162 adoption pack, current proof dependency graph, public verifier endpoints, role obligations, creator audit paths, regulator exports, copied-output status links, and settlement holds must be bound into one acyclic public root before any participating AI route can claim source-footer confidence, copied-output reliance, or direct creator settlement. This makes the footer a verifiable industry object, not a provider local UI convention. L164 closes the installability gap: the L163 root must be packaged into signed, reproducible SDKs, gateway middleware, MCP adapters, OpenTelemetry mappings, C2PA assertions, W3C VC trust marks, SCITT statements, settlement adapters, offline verifier containers, CI workflows, procurement policies, and SBOM/SLSA provenance. This prevents a provider from claiming adoption with custom, unreviewed glue code that strips source footers, telemetry, proof downloads, or settlement holds. L142 specifically closes the semantic-cache bypass by requiring reused answers to replay evidence overlap, citation continuity, source freshness, consent/license state, collision resistance, and a new royalty-metered reuse event. L143 closes the training-to-serving bypass by requiring training-stage obligations, post-training signal lineage, model release bindings, provider routes, visible citation contracts, grounded reuse contracts, revocation propagation, residual royalties, valuation methods, and serving meters to agree before a foundation-model answer can claim attribution or settlement. L144 closes the private-evidence trust gap by requiring L143 claims to bind to confidential evidence-room commitments, proof mechanism handles, independent auditor quorum, creator challenge routes, regulator export support, and fail-closed leakage controls before private training, post-training, serving, or valuation evidence can support attribution or direct settlement. L145 closes the runtime-authority gap by requiring model APIs, agent runtimes, tools, retrieval connectors, memory stores, browser/file/code actions, enterprise gateways, and settlement gateways to bind source attribution, source footer release, tool use, memory use, model invocation, inference chains, intervention logs, revocation checks, and settlement authority before a response or payout can be released. L146 closes the deployment-root gap by binding certification, provider disclosure, integration, discovery, assurance, proof graph, source-footer, training-to-serving, confidential-audit, authority, and settlement posture into one provider-neutral root. L147 closes the runtime-emission gap by requiring each actual response to bind that root to the release gate, proof-carrying response, serving gateway, delivered source footer, live witness, transparency log, invocation witness, foundation runtime route, and client display enforcement before the answer may claim grounded attribution or creator settlement. L148 closes the adoption-completeness gap by requiring the provider's universal passport, adoption standard, interop kit, L146 root, L147 gateway, source footer, client display enforcement, provider-family rows, native API bindings, telemetry mapping, customer surfaces, standards bridges, and fail-closed negative cases to verify as one composite contract before the deployment may claim universal RDLLM compatibility. This is the layer that turns "the answer has a source footer" into "the provider route, client display, telemetry, settlement, and public verifier surface all agree on the same source-footered answer." L149 closes the deployment-runtime gap by requiring the actual runtime receipt to bind provider API routes, generation entrypoints, tool/agent routes, source attribution modes, claim-source verification, visible footer injection, client display enforcement, OpenTelemetry GenAI export, proof download, challenge routing, privacy filtering, and settlement metering before a response can be shown as grounded or paid. This is the layer that turns "the provider contract is complete" into "this answer's footer, sources, telemetry, and payout meter were enforced on the route that produced it." L150 closes the post-hoc citation gap by requiring a generation-time claim provenance envelope. Each answer claim or sentence must bind a support relation such as quotation, compression, inference, retrieval, tool observation, conversation memory, parametric memory, or residual corpus value to a source proof hash, exact evidence-region binding, citation identity, evidence locator, URL-health result, visible footer row, tool or memory trace, payout basis, and settlement meter before display. If a provider attaches plausible citations after generation, strips the footer row, fabricates a locator, cannot link a tool observation to the claim, or attempts direct settlement without verified claim support, the envelope blocks display and payout.

L151 closes the provider-transport gap by requiring a universal provider wire protocol. Every supported foundation-model API binding must carry the L150 envelope hash, L149 runtime receipt hash, footer metadata, stream checkpoints, tool-call mappings, transform receipts, telemetry spans, and settlement meters through request headers, response headers, JSON bodies, SSE streams, SDK metadata, gateway/proxy rewrites, batch callbacks, webhooks, and exported copies. If a provider SDK, aggregator, proxy, or export path drops or rewrites attribution metadata without a transform receipt, the route cannot claim grounded display or direct creator settlement.

L152 closes the accountability-chain gap by requiring one append-only audit trail that binds provider-wire calls to governance approvals, policy versions, delegated agents, tool calls, memory reads and writes, footer rendering, exports, challenge/correction events, and settlement meters. The public artifact contains hashes, actor roles, commitments, and verifier commands rather than raw prompts, outputs, source text, tool payloads, customer records, or payment data. If the event sequence is non-monotonic, a previous-event hash is missing, an actor lacks authority, a governance waiver lacks an attestation, a tool or memory action lacks causal attribution, or settlement occurs without an audit event, the trail blocks grounded display and direct creator settlement.

L153 closes the split-view accountability gap by requiring the L152 audit-trail root and related settlement, footer, governance, redaction, revocation, and challenge checkpoints to be published to transparency logs with inclusion and consistency proofs. The quorum requires independent auditor, creator-collective, customer, regulator-observer, and public-interest witnesses, plus monitors that can detect stale checkpoints or different log roots shown to different parties. This maps Certificate Transparency/RFC 9162, SCITT/RFC 9943, Sigstore/Rekor, C2SP checkpoint/witness practice, transparency-dev verifiable data structures, and witness cosigning into one settlement rule: no witnessed L152 checkpoint, no trusted attribution display and no direct creator settlement.

L154 closes the grounded-reliance gap by requiring the witnessed L153 root to be joined with source verification, source-confidence floors, citation-footer contracts, delivered client footers, evidence locators, citation URL-health, claim coverage, context closure, sufficiency, counterevidence, freshness, evidence-force calibration, warranted footer labels, source-origin lineage, revenue allocation, and finance-ledger attestation. The result is a compact public contract that says which source footers, confidence labels, procurement claims, regulator exports, and creator settlement rows can be relied on. If a citation is merely linked but not support-verified, stale, unrendered, overclaimed, unverifiable, or unwitnessed, the contract blocks reliance.

Earlier layers covering source-origin lineage, evidence-preview footers, evidence-locator manifests, citation URL-health reports, composite foundation adapters, foundation provider conformance matrices, foundation runtime adapter receipts, and foundation runtime router receipts: providers must first reconcile source confidence, authenticity, evidence sufficiency, counterevidence, pinpoint provenance, and citation identity into one attribution consensus report. Direct settlement then requires an independent verifier quorum report with multiple external signed replay attestations over the same artifact root. The next gate binds those accepted verifier rows to active trust-registry identities, non-revoked key hashes, slashable bond coverage, conflict disclosures, and no blocking accountability challenge. The next gate requires required usage receipts to appear in append-only transparency-log snapshots with valid inclusion proofs and no split-view roots. The final gate requires registered independent watchtower attestations over that receipt transparency subject and blocks direct payout while any public challenge is open or accepted. The L75 gate then binds copied or exported output to proof-carrying responses, serving-gateway output hashes, attribution capsules, watchtower-cleared settlement, content credentials, watermark commitments, fingerprint commitments, and public verification paths. The L76 gate then publishes those late-bound output proof artifacts through a post-release discovery report without mutating the base discovery manifest or introducing a self-referential proof graph. The L77 gate then reconciles the instruction-only remittance file against hash-only external payment and escrow processor records, rejects duplicate, unmatched, amount-drifted, wrong-account, or raw-bank-input records, and preserves holds as unpaid carryforward rows. This turns the recent citation-verification lesson into a royalty control: a footer that looks plausible is not enough unless independent verifiers can replay the source evidence, sign the result, carry accountable economic consequences for bad or conflicted attestations, prove that the same economic usage history was shown to creators, customers, providers, and witnesses, and prove that payout instructions were actually executed or escrowed before settlement is described as paid. The L78 gate then requires registered payment or escrow processors to sign the settlement batches that back those execution rows; public verifiers check processor registry status, allowed role, signature validity, batch coverage, hashes, totals, statuses, and absence of raw payment data. The L79 gate then emits creator-facing payout receipts that bind each credited work and clearinghouse settlement row to the remittance instruction, execution row, signed processor batch, and paid, escrowed, or held status. Public verification can prove the creator's receipt without exposing prompts, source text, customer data, tax data, or raw bank details. The L80 gate then parses the exact visible Markdown answer, source footer, and claim-evidence rows. It verifies inline [S#] markers, footer rows, source URIs, content-hash prefixes, and claim span prefixes against the response envelope, citation footer contract, source availability, evidence sufficiency, counterevidence, and answer-coverage artifacts. This closes the gap between "sources exist somewhere in the proof pack" and "the user-visible answer is actually grounded by those same sources." The L81 gate then scans the exact displayed answer against registered source snapshots and requires any detected memorized training span to be visible in the footer, present in the training-content summary, covered by a creator-license contract, and safe for training, generation, and display. This incorporates the OLMoTrace lesson that output text can be traced back to training data and the DataDignity lesson that true provenance must distinguish answer-critical support from topical similarity. The L82 gate then requires each support-bearing answer unit to be locked to source evidence, context closure, footer display, and rendered claim-evidence rows before generation starts. This turns citation verification from a post-hoc formatting check into a pre-generation constraint. The L83 gate then binds proof-carrying response delivery, serving-gateway egress, streaming chunks, and the L82 lock rows to the same output hash. This moves the mechanism from "a valid evidence lock exists" to "the emitted response path used that lock before chunks left the serving boundary." The L84 gate then requires independent witnesses to sign preflight and completion subjects over the stream boundary. The L85 gate then requires those witness subjects and all witness attestations to appear in append-only transparency logs with valid inclusion proofs, append-only prefix consistency, and no split-view roots. This moves the mechanism from "independent observers saw the stream" to "the provider cannot selectively suppress or fork those observer records." The L86 gate then binds that live-transparent output path to a measured runtime, model binding, policy bundle, verifier bundle, nonce, trusted attestor identity, and required attribution capabilities. This closes a remaining trust gap: a provider cannot claim that the proof-carrying response, evidence locks, footer contract, gateway, witnesses, and transparency logs were enforced by the serving runtime unless the runtime measurement and attestor quote verify against the same subject binding root. The L87 gate then independently replays each visible claim against candidate sources, Q&A nugget commitments, topical anti-documents, optional visual-region commitments, and LOO-style source contribution before accepting a footer row or direct payout. This closes the remaining user-confidence gap: a cited footer row is not enough unless the claim, source, visual anchor when applicable, attribution credit, and escrow/refusal decision can all be replayed without raw prompt, answer, source, claim, nugget, or visual-region text leaking into the public report. The L88 gate then binds each credited footer row to current-turn retrieval/tool trace commitments and causal intervention trials. REMOVE and REPLACE trials must show that the source mattered, DUPLICATE trials must not increase credit, and multi-source removal trials can prove synergistic evidence for multi-hop answers. This closes the gap between "the source supports the text" and "the model actually used this source in this answer," while rejecting prior-context citation drift, spurious citations, duplicate over-credit, and public leakage of raw prompt, answer, source, claim, query, or observation text. The L89 gate then handles claims sourced from model weights rather than current retrieval. It binds each accepted source to a training-content summary, memory recall probes, influence or model-signal evidence, anti-document separation, and a current-context contamination check. Sources retrieved in the same turn cannot receive parametric credit; they must pass the L88 evidence-utility path instead. The L90 gate then handles non-verbatim creative imitation. It emits a rdllm-style-influence-attribution/v1 report that credits a registered style or voice profile only when the profile is licensed for the attempted use, the output has sufficient style or media-signature similarity, the prompt or request carries declared style intent, anti-style decoys are separated, and content-copy overlap stays below the semantic/copy attribution threshold. Copy-like outputs route away from style payout, revoked or unsupported licenses route to escrow, and accepted style rows produce footer rows without exposing private style exemplars or output text. The L91 gate then handles downstream models trained, fine-tuned, or distilled from attributed outputs or synthetic datasets. It emits a rdllm-model-lineage-attribution/v1 report that binds the student model, training run, training-content summary, synthetic disclosure, teacher-distribution or teacher-output evidence, source rows, duplicate artifact guard, and future usage event into one settlement surface. Accepted training items route a configured model-lineage share of downstream creator-pool value back to upstream creators; revoked or unsupported source rows route to escrow; duplicate artifacts are held so repeated synthetic rows cannot inflate credit. Hidden synthetic training or missing teacher evidence fails the certification gate. The L92 gate then handles undisclosed derivative models exposed only through black-box APIs. It emits a rdllm-black-box-model-provenance/v1 report that binds challenge prompt hashes, challenged-output hashes, candidate model commitments, baseline score distributions, empirical and adjusted p-values, watermark or behavior-fingerprint support counts, candidate provenance-set rows, source footers, and unresolved derivative payout or escrow obligations without exposing private prompts, source text, or model outputs. The L93 gate then handles disputes over those attribution decisions. It emits a rdllm-attribution-dispute-adjudication-report/v1 artifact that binds the subject proof hash, claimant rows, respondent rebuttal rows, public evidence commitments, bonded verifier votes, conflict disclosures, appeal status, escrow release rows, freeze rows, slash rows, bounty rows, and adjudicated footer rows. Verification rejects missing notice, insufficient evidence commitments, failed quorum, conflicted quorum votes, premature release during appeal, unconserved escrow, settlement rows that do not match the decision, and any private prompt, source, output, or challenge transcript leakage. The L94 gate handles the accounting problem that remains after adjudication: payment processors and creator statements may already have executed older settlement rows. It emits a rdllm-post-adjudication-settlement-adjustment-report/v1 artifact that binds the L93 adjudication hash, original payment or payout-receipt hashes, corrected entitlement rows, creator deltas, top-up rows, recoupment rows, future-netting rows, appeal freeze rows, and creator-visible adjustment receipts. Verification rejects historical payment rewrites, missing processor or receipt hashes, uncapped recoupment, top-ups not covered by escrow, appeal-time release, unconserved adjustment totals, missing creator receipts, and private payment or source-evidence leakage. The L95 gate handles diffuse licensed training-corpus value that cannot honestly be tied to a single visible answer source. It emits a rdllm-residual-corpus-royalty-report/v1 artifact that binds model-usage revenue rows, training-content summary cohorts, creator-license terms, valuation evidence hashes, direct-attribution exclusions, creator-level caps, payable rows, escrow rows, and creator residual receipts. This does not replace source footers: runtime citations and claim-level footers remain the user-facing attribution surface, while residual corpus royalty is a separate pool for licensed training-value influence. Verification rejects unreproducible training/license hashes, unlicensed or low-confidence valuation rows paid directly instead of escrowed, direct answer attribution double counting, creator-cap violations, unconserved residual pools, missing receipts, and public leakage of prompt, output, source, training, customer, or payment text. The L96 gate audits the valuation method itself before residual-corpus royalty rows are accepted. It binds the L95 residual report to public method cards, benchmark case hashes, known-contributor checks, hard anti-document rejections, duplicate-inflation guards, confidence calibration, score-stability rows, method-code/evidence commitments, and privacy or zero-knowledge proof commitments. Verification rejects unaudited residual valuation methods, benchmark drift, duplicate over-credit, unstable scores, missing privacy commitments, and any raw benchmark, training, prompt, output, customer, or payment text in the public report.

Sources: YouTube Help, "Monetisation during Content ID disputes"; C2PA Conformance Program; IETF SCITT/RFC 9943; RFC 9162 Certificate Transparency; RFC 7517 JSON Web Key; W3C DID Core; Sigstore TUF trust root; Sigstore Rekor; transparency-dev witness; in-toto; confidential-computing remote attestation patterns; Attestation Framework; IETF RFC 9901; W3C Verifiable Credentials Data Integrity; ISO 20022 Payments Initiation; OpenTelemetry GenAI Semantic Conventions; Strauss et al., "The Attribution Crisis in LLM Search Results" (2026); Onweller et al., "Cited but Not Verified" (2026); CiteCheck (2026); CiteAudit (2026); PaperTrail (2026); SciTrue (2026); DAVinCI (2026); CUE-R (2026); TRACER (2026); SCITT/RFC 9943 (2026); OLMoTrace (2025); DataDignity (2026); SourceBench (2026); HybridSourceTracker (2026); CiteTracer (2026); Attribution Contract (2026); Lei et al., "PrivaRisk" (2025); PrivChain-AI (2026); Wallat et al., "Correctness is not Faithfulness in Retrieval Augmented Generation Attributions" (2025); OWASP LLM01:2025; Chaturvedi et al., "AIP" (EMNLP 2025); Khodayari et al., "Indirect Prompt Injection in the Wild" (2026); ARGUS (2026); AuthGraph (2026); Geissler et al., "Towards Dependable Retrieval-Augmented Generation Using Factual Confidence Prediction" (2026); Gur-Arieh et al., "Faithfulness Metrics Don't Measure Faithfulness" (2026); RAGVUE (2026); Nikolic et al., "Provenance Testing of Generated Models" (2025); Sander et al., "TextSeal" (2026); Luan et al., "VOW" (2026); Xu et al., "Behavioral Fingerprinting of Language Models" (2026); Li et al., "Text-Preserving Audit" (2025).

RDLLM now also emits integration profiles, discovery manifests, lineage reports, media attribution reports, model signal attribution reports, rights remediation reports, semantic text attribution reports, code attribution reports, claim verification reports, source availability reports, evidence sufficiency reports, counterevidence reports, answer claim coverage reports, rendered attribution audits, generation context closure reports, source boundary reports, decision provenance reports, calibrated attribution reports, release-grounding closure checks, creator license contracts, source confidence reports, attribution exchange manifests, conformance vector packs, federation handshakes, attribution capsules, transitive attribution reports, clearinghouse reports, remittance reports, payment execution reports, attested attribution runtime reports, claim-source attribution reports, evidence-force calibration reports, warranted source footer reports, source-origin lineage reports, audit attestations, revenue allocation reports, finance ledger attestations, proof dependency graphs, publication monitors, publication witnesses, and trust registries, attribution dispute adjudication reports, and post-adjudication settlement adjustment reports so attribution is not merely a set of proof files, but a provider-facing contract, well-known verification entry point, upstream-obligation trail, downstream relay contract, cross-provider settlement artifact, payment-instruction artifact, independent audit artifact, pre-settlement revenue allocation artifact, source availability artifact, evidence-sufficiency artifact, counterevidence artifact, answer-coverage artifact, rendered-answer attribution artifact, release-gate grounding-closure artifact, decision-provenance artifact, calibrated-attribution artifact, and finance-ledger reconciliation artifact, replay-order artifact, append-only publication history, anti-equivocation witness artifact, and signer trust-root artifact that model APIs can publish, negotiate, copy forward, clear, remit, and verify at runtime.

Dataset and AI Bill-of-Materials Standards

MLCommons Croissant provides machine-readable dataset metadata, including provenance and permissions, and is already supported across major dataset repositories. Croissant 1.1 adds structured usage policies for automated enforcement of consent and licensing. SPDX 3.0 adds AI model and dataset bill-of-material concepts. Royalty Driven LLM receipts should interoperate with these formats so source owners can be tracked from dataset registration through training, retrieval, generation, and settlement.

Sources: MLCommons Croissant 1.1 specification; SPDX 3.0.1 specification.

Policy Direction

The EU AI Act requires general-purpose AI model providers to put in place a copyright policy and publish a sufficiently detailed summary of content used for training. The European Commission's 2026 FAQ says the public training-content template is mandatory under Article 53(1)(d), and should be updated at six-month intervals or sooner for material changes. The U.S. Copyright Office's 2025 report on generative AI training frames the central policy question as whether consent or compensation is needed for copyrighted works used in AI systems, and discusses voluntary licensing, collective licensing, and statutory options.

Sources: European Commission Q&A on general-purpose AI models in the AI Act; U.S. Copyright Office, "Copyright and Artificial Intelligence, Part 3: Generative AI Training" (2025).

Creator Need

Creative workers have directly asked for consent, credit, and compensation in generative AI governance. Kyi et al. report interviews with creative workers and identify gaps between current AI governance and creators' expectations around consent, compensation, and credit.

Source: Kyi et al., "Governance of Generative AI in Creative Work" (CHI 2025).

Bottom Line

No cited source alone proves that an AI royalty market is already solved. Together, they prove the main premises:

1. Creator revenue sharing at platform scale exists.
2. Automated rights identification at platform scale exists.
3. Data valuation and training influence have a research base.
4. Provenance has mature technical standards.
5. Transparency logs and supply-chain attestations provide a proven verification model.
6. Dataset metadata and AI-BOM standards are becoming machine-readable.
7. Rights-expression standards can encode allowed use, prohibited use, and duties.
8. Verifiable credential standards can carry portable ownership attestations.
9. PROV-style graphs can make answer-level attribution inspectable by systems beyond the original model provider.
10. AI policy is moving toward copyright transparency and licensing.
11. Creators are explicitly demanding consent, credit, and compensation.
12. Model-internal attribution research is mature enough to expose provider-private influence signals as verifiable commitments rather than public raw activations.
13. Payment and credential standards are mature enough to represent remittance instructions, end-to-end reconciliation IDs, and portable signed claims without disclosing raw creator payment accounts.

The repository's code turns those premises into a concrete mechanism that can attribute retrieval use, generated text overlap, citations, training-value priors, claim evidence span hashes, rights-policy decisions, rights-conflict escrow, and unattributed escrow across AI products. The latest implementation also blocks direct settlement to duplicate ownership claimants through registry-dispute escrow. It then releases that escrow only through verifiable settlement reports. It renders grounded answers with source footers, so attribution benefits both creators and end users. It now also exports portable VC/PROV-style artifacts so the attribution trail can leave the originating API and be independently checked. It now also emits privacy-preserving royalty statements so creator payouts can be audited at platform scale without publishing prompts, outputs, quotes, evidence text, or matched text. It now also emits public assurance bundles so a regulator, creator, or customer can verify that the proof pack was published intact without receiving the private payloads behind each artifact. It now also emits answer provenance cards so the user-facing footer is itself a verifiable artifact, not only explanatory text in a model response. It now also emits source verification reports so cited sources are materialized against registered content hashes rather than trusted because they look plausible. It now also emits source confidence reports so the public footer itself carries a verified/warning/failed status, claim confidence rows, and a hallucination taxonomy before users are asked to trust the sources shown under an answer. It now also emits citation footer contracts so the exact source rows and claim anchors that users see are signed, hash-bound, license-aware, royalty-aware, and rejected if they drift from the public response proofs. It now also emits response envelopes so API customers receive the answer and its public verification pack as one reproducible object. It now also emits model signal attribution reports so providers can prove which registered works influenced a generated answer through private telemetry commitments, while users still receive grounded source footers and source verification reports. It now also emits remittance reports so clearinghouse obligations become instruction-only payment rows with payout-account hashes, ISO 20022-compatible references, preserved holds, and verifier checks before any payment processor moves funds. It now also emits payment execution reports so those instruction-only rows are reconciled against hash-only processor and escrow settlement records before payouts are treated as executed. It now also emits payment rail attestations so registered external payment or escrow processors must sign the settlement batches behind those execution rows before payout finality is trusted. It now also emits third-party audit attestations so independent reviewers can replay the public proof pack, verify discovery and integration surfaces, detect footer, remittance, payment-execution, or payment-rail drift, and cite a hash-only readiness report without seeing private prompts, answers, source text, evidence text, or payout accounts. It now also emits publication monitors so customers, creators, downstream providers, and auditors can track public proof-surface drift over time and reject certification regressions without seeing private payloads. It now also emits watchtower challenge settlement reports so clean receipt-log consistency is not merely passive: registered independent watchtowers must attest to the L73 subject, and open or accepted challenges force creator value into escrow with hash-only slashing and bounty evidence. It now also emits output provenance binding reports so copied text, exported files, search snippets, and platform reposts can be checked against content credentials, watermark commitments, fingerprint commitments, and the public RDLLM proof surface without exposing raw generated text. It now also emits post-release discovery reports so those late-bound output proof artifacts are discoverable from the public RDLLM surface without rewriting the base manifest or creating a hash cycle. It now also emits composite foundation adapter reports so the same attribution contract can be verified across provider-native API shapes instead of depending on one vendor's response format. It now also emits foundation provider conformance matrices so every supported provider family publishes hash-only positive and negative fixtures for attribution critical response modes before claiming L126 compatibility. It now also emits foundation runtime adapter receipts so a native provider response must prove its concrete headers, JSON proof hashes, stream-final metadata, citation paths, URL-health proof, and footer bindings before any user-visible release. It now also emits foundation runtime router receipts so provider fallback, latency/cost routing, and model selection cannot become attribution bypass paths. It now also emits foundation model deployment attestations so backend model substitution cannot bypass attribution after a route has been selected. It now also emits universal composition receipts so multi-provider synthesis, fallback stitching, or delegated answer assembly cannot drop source footers, telemetry spans, or creator-value shares from any participating provider segment. It now also emits universal composition settlement receipts so those source footer rows and provider-segment shares clear into payable, escrowed, or held creator obligations under a conserved revenue allocation pool. It now also emits universal foundation model contracts so OpenAI-style, Anthropic-style, Gemini-style, Bedrock-style, Azure/OpenAI-compatible, xAI, Cohere, Mistral, Meta/Llama-style, and other supported foundation-provider families must all bind to the same RDLLM adapter, conformance, routing, deployment, composition, settlement, discovery, and public-surface proof chain before release. It now also emits universal invocation guards so raw provider calls cannot bypass that proof chain: each invocation must pass fail-closed preflight headers, request/response boundary checks, source-footer requirements, and GenAI telemetry binding before a native model call is allowed. It now also emits universal invocation coverage reports so complete deployments must reconcile every native provider meter event against one L133 guard, gateway egress record, source-footer binding, response-envelope binding, and invoice row. It now also emits universal invocation witness reports so complete deployments can prove L134 coverage is supported by provider-signed usage receipts, independent egress observations, and independent witness quorum evidence. It now also emits universal content credentials so released or copied answers carry one portable proof object binding visible sources, evidence previews, locator and URL-health evidence, creator payout eligibility, provider invocation evidence, content credentials, watermark/fingerprint signals, and public verifier surfaces. It now also emits universal reliance correction ledgers so the footer does not freeze trust at first publication. Every L154 reliance contract is bound to live status rows for active, corrected, revoked, downgraded, superseded, held, adjusted, and regulator-notice states; correction broadcasts reach well-known feeds, response metadata endpoints, client SDKs, caches, copied-output capsules, creators, customers, and regulators; stale citation, URL, freshness, counterevidence, license, confidence, render, and settlement checks rerun continuously; and any revoked source footer or stale copied output blocks display, cache reuse, or settlement release until the status ledger records a reconciled hold or adjustment.