Recent Research Notes: Grounded Attribution for AI Outputs

This note captures recent primary sources that directly shaped the current mechanism. The conclusion is clear: payout attribution and user-facing source attribution should share the same evidence trail.

2026-07-10 RDLLM 1.0 Evidence Boundary

Four recent papers sharpen the 1.0 design. Cited but Not Verified shows that working and relevant links can coexist with substantially weaker factual support. How Do LLMs Cite? shows why visible citation behavior is not proof of the model's internal computational reliance. Data Attribution in Large Language Models via Bidirectional Gradient Optimization treats training-data influence as a distinct, model-access-dependent problem. What's a Credit Worth? shows that the informativeness of an attribution signal can change whether royalty or fixed-fee compensation is economically preferable.

RDLLM 1.0 therefore separates three evidence classes:

Unsupported, over-warranted, post-hoc, or disputed claims do not become direct settlement. The event records review or escrow, and direct execution remains disabled. Production deployment claims now require Ed25519-signed evidence from trusted external issuers; direct payout additionally requires a trusted payment processor attestation. Bundled profiles deliberately contain no such external evidence and cannot self-certify production readiness.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2606.28358, https://arxiv.org/abs/2606.04928, and https://arxiv.org/abs/2607.00641.

2026-07 GitHub, SEO, and GEO Documentation Update

The onboarding surface now treats documentation as part of the product boundary. Google's Search Central guidance frames SEO as making content easier for search engines to crawl, index, and understand while still serving users first. The GEO paper frames generative engines as systems that synthesize answers from multiple sources and need citation precision and recall. Stack Overflow's 2025 Developer Survey also shows why examples need to meet builders in common implementation languages rather than only in the Python library path. 2026 language-speaker rankings provide the basis for concise global quickstarts.

The repository therefore adds a GitHub start guide, live runtime use cases, five implementation-language API examples, a public explanation ladder, and localized quickstarts plus explainers in 15 languages. The new github_docs_readiness_audit gate checks that these surfaces keep source footers, Claim Evidence, support metrics, payout fields, and source-disagreement status visible. This is not a ranking guarantee; it is a maintenance rule that keeps the public docs crawlable, citeable, and useful to a developer who has never seen RDLLM before.

References: https://developers.google.com/search/docs/fundamentals/seo-starter-guide, https://arxiv.org/abs/2311.09735, https://survey.stackoverflow.co/2025/technology, and https://en.wikipedia.org/wiki/List_of_languages_by_total_number_of_speakers.

2026-07 Production-Readiness Update

The production target is an open-source attribution platform that can be operated by individuals, companies, institutions, governments, model providers, and public sector deployments. The mechanism therefore adds a separate production-readiness gate for live operation. This gate is distinct from the artifact ship gate: it requires an operator profile, tenancy controls, runtime admission controls, source-footer enforcement, rights governance, dispute escrow, payment or instruction-only settlement controls, incident response, backup testing, public-sector controls, and public proof surfaces.

Those profile controls establish configuration readiness only. RDLLM 1.0 also requires current external attestations verified against an independently managed trust store before it permits a production-grade claim.

The controls are anchored to NIST AI RMF GenAI Profile, NIST SSDF, OWASP Top 10 for LLM Applications 2025, and SLSA because RDLLM production readiness is not only a model-quality claim. It is an operational claim about secure software, AI-risk controls, source-grounding integrity, supply-chain provenance, privacy, and auditable settlement.

2026-07 Runtime Display-Surface Update

Recent citation-failure work pushes the runtime boundary beyond "there is a footer object somewhere in the JSON." Cited but Not Verified separates link validity, relevance, and factual support; Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents shows that source-looking URLs can be fabricated or stale even in search/deep-research systems; CiteCheck separates real citations from metadata drift and fabricated references; CiteGuard treats citation validation as retrieval-grounded attribution alignment; and Correctness is not Faithfulness in RAG Attributions shows why post-rationalized citations can look correct while not reflecting model reliance.

The production rule is therefore that a response is not ready for display unless the client-renderable answer surface is bound to the event hash and source-footer hash. The service response now carries display.rendered_text, a display_hash, and an answer_plus_verified_source_footer render policy. rdllm-service-response-verify recomputes the display surface from the raw answer and verified footer rows, then fails if the rendered answer/footer surface is missing, modified, or detached from the summary hash. This keeps user trust anchored to the exact answer the client can render, not to a hidden payout ledger or decorative citation list.

2026-07 Inline Citation Marker Gate Update

Recent source-attribution results make one additional production rule necessary: the answer text cannot contain citation-shaped markers that fail to resolve to the verified footer. Cited but Not Verified shows that link validity and topical relevance can mask much lower factual support, FACTUM treats citation hallucination as distinct from generic RAG hallucination, SourceCheckup reports large unsupported-statement rates even when answers cite sources, and sub-sentence citation work argues that users need concise, sufficient evidence anchors rather than broad citation spans.

The service therefore now treats unresolved inline markers such as [2], [Source: 3], or [S9] as display-blocking audit errors unless they match a verified source-footer source label or supported claim label. Numeric markers resolve as source aliases, so [1] and [Source: 1] are accepted only when verified source row S1 exists; numeric groups and ranges must fully resolve, while four-digit bracketed years are ignored as non-citation text. The response verifier publishes answer_citation_marker_count, resolved_answer_citation_marker_count, citation_marker_status, and detected/resolved/unresolved marker lists inside source_grounding_acceptance, so operators can distinguish a grounded answer with no inline markers from one that contains misleading citation-shaped text.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2601.05866, https://www.nature.com/articles/s41467-025-58551-6, and https://arxiv.org/abs/2509.20859.

New deep-research citation papers add a display gap that bracket-marker parsing does not cover: generated answers can include Markdown links or bare URLs that look like source citations while bypassing the verified footer. Cited but Not Verified evaluates inline citations in Markdown reports by parsing the generated report, retrieving cited content, and separating link accessibility, topical relevance, and factual support. ProvenAI similarly separates answer correctness, citation fidelity, and document influence, showing that clean surface citation audits can coexist with weak influence from cited sources. How Do LLMs Cite? reinforces the product risk: inline citations can create a false sense of security when citation behavior is not proof of source use.

The service therefore now treats answer-link URIs as a production display gate. Any scheme://... URI in the generated answer, including Markdown links, must match a verified footer source_uri; otherwise attribution returns a blocked response and rdllm-service-response-verify fails ready responses. The verifier publishes answer_link_uris, resolved_answer_link_uris, unresolved_answer_link_uris, URI counts, and answer_link_status inside source_grounding_acceptance. This does not claim the linked page is factually sufficient by itself; it prevents generated answers from introducing foreign source-looking locators outside the auditable footer.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2606.26449, and https://arxiv.org/abs/2606.28358.

2026-07 Answer-Claim Coverage Update

Recent claim-level verification work shows why valid source rows are not enough: the displayed answer can contain extra factual units that never receive a claim-evidence row. PaperTrail decomposes LLM answers and source documents into discrete claims and evidence to reveal unsupported assertions and omissions. MedRAGChecker similarly treats generated biomedical answers as atomic claims and aggregates claim decisions into answer-level diagnostics. The Google AI Overviews measurement study decomposed generated responses into 98,020 atomic claims and found unsupported claims even when cited pages were high quality, showing that source quality and claim fidelity are separate dimensions.

The service verifier now exposes answer-claim coverage inside source_grounding_acceptance. It recomputes answer claim units from event.answer_text, compares their hashes with footer claim_rows, and reports answer_claim_unit_count, answer_claim_row_coverage_count, uncovered_answer_claim_hashes, extra_claim_row_hashes, and answer_claim_coverage_status. A ready response fails verification if answer text claims and footer claim rows do not match exactly. This is a display integrity gate: it prevents rehashed responses from adding unsupported answer text outside the footer; the existing claim-evidence and support-score gates still decide whether each covered claim is strongly supported.

References: https://arxiv.org/abs/2602.21045, https://arxiv.org/abs/2601.06519, and https://arxiv.org/abs/2605.14021.

2026-07 Evidence-Force Calibration Update

Recent cited-RAG evaluation work shows that claim coverage is still too weak when a source is merely related to a claim. Relevant Is Not Warranted frames this as citation laundering: the evidence may be real and relevant while failing to warrant the exact force of the attached wording. Its FORCEBENCH stress test uses five localized force axes: relation, modality, scope, temporal validity, and numeric specificity. Know Before You Fetch also argues for calibrated interfaces that make retrieval and abstention decisions explicit rather than treating a raw score as a universal confidence signal.

The service footer therefore now renders claim-level warrant metadata. Each Claim Evidence row includes claim_preview, claim_warrant_profile, claim_force_flags, evidence_force_flags, warrant_mismatch_flags, and warrant_strength_status. The response verifier recomputes those fields from the claim and evidence text, fails grounded display when a supported claim's evidence does not carry the same relation/modality/scope/temporal/numeric force, and exposes claim_warrant_strength_status inside source_grounding_acceptance. The public source-footer verifier enforces the same gate for copied/exported footer artifacts. This moves RDLLM from "there is a related evidence span" to "the evidence visibly warrants the strength of the displayed claim."

References: https://arxiv.org/abs/2605.28044, https://arxiv.org/abs/2606.29959, and https://arxiv.org/abs/2605.06635.

2026-07 Visible Source-Disagreement Update

Recent conflict-aware RAG work adds a transparency requirement beyond source support: systems should not assume retrieved or visible sources agree with each other. ConflictRAG explicitly detects, classifies, and resolves knowledge conflicts before answer generation. ArbGraph separates evidence arbitration from generation by building support/contradiction relations over atomic claims. Contradiction to Consensus shows why single-source verification is insufficient: claim verification should retrieve both original and negated perspectives and expose source-level disagreement.

The service footer now renders conservative source-disagreement metadata in Claim Evidence rows. Each supported claim carries source_disagreement_profile, agreement_source_labels, disagreement_source_labels, and source_disagreement_status. The verifier recomputes those fields from the visible source rows and fails grounded display when a high-overlap visible source has opposite negation polarity for the claim. The public source-footer verifier enforces the same gate for copied/exported footers. This does not claim complete semantic conflict resolution; it prevents the product from presenting a claim as cleanly grounded while a visible source plainly says the opposite.

References: https://arxiv.org/abs/2605.17301, https://arxiv.org/abs/2604.18362, and https://arxiv.org/abs/2602.18693.

2026-07 Model-Reliance Claim Discipline Update

Recent attribution and explanation papers add a separate trust risk: answer text can imply that the model internally used, reasoned over, or was influenced by a source even when RDLLM has only observable source-support and allocation evidence. How Do LLMs Cite? shows that citation behavior can diverge from the model's internal computational pathway. ProvenAI separates citation fidelity from per-document influence and gives examples where cited and influential evidence diverge. Evaluating the False Trust Engendered by LLM Explanations shows that reasoning traces and post-hoc explanations can persuade users without being faithful provenance.

The service now blocks model-internal reliance claims on the public answer surface. Phrases such as I used, my reasoning, or sources shaped the answer fail display unless they are removed from the answer and represented instead as observable footer support/allocation fields or as a separate, verifiable model-signal artifact. source_grounding_acceptance publishes model_reliance_claim_markers, model_reliance_claim_marker_count, and model_reliance_claim_status, so operators can distinguish "this claim is supported by a footer row" from the stronger and usually unverifiable statement "the model internally relied on this source."

References: https://arxiv.org/abs/2606.28358, https://arxiv.org/abs/2606.26449, and https://arxiv.org/abs/2605.10930.

2026-07 Source-Usage Transparency Update

The latest papers point to a second display problem: even when the footer source is real and claim-support verified, users still need to know what role the source played in the answer. Explicit Evidence Grounding via Structured Inline Citation Generation reports that document-level citation is easier than precise evidence-span grounding; How Do LLMs Cite? warns that inline citations can create a false sense of security because citation behavior may not reflect the internal computation path; VERICITE shows that sentence-level citation support can remain low even with retrieved medical abstracts; and What's a Credit Worth? argues that noisy attribution signals materially change whether royalty or fixed-fee compensation is welfare-optimal. A Human-Centric Framework for Data Attribution in Large Language Models also frames attribution as a negotiated stakeholder contract rather than a single universal score.

The runtime now renders source-usage metrics directly in service footers. Each visible source row includes support, text_match, weight, and payout, alongside source identity, verification handle, claim count, confidence, selection rationale, settlement state, and content hash. These fields are recomputed by both the saved response verifier and the public source-footer verifier, so a copied or exported answer cannot silently replace the user-facing usage explanation. source_grounding_acceptance now also reports source_usage_metric_names, source_usage_metric_row_count, and source_usage_metric_status, failing grounded display when a visible source row does not expose the required usage/allocation metrics. The same verifier now publishes claim_evidence_row_count and claim_evidence_status; every supported claim must expose a visible Claim Evidence row whose claim hash, support score, evidence span hash, character offsets, and evidence preview recompute from the footer payload. That closes the gap between source-level allocation and sentence- or claim-level factual support. RDLLM still distinguishes observable attribution and settlement allocation from hidden model-internal reliance; internal usage should only be claimed when provider model-signal telemetry is separately verified.

References: https://arxiv.org/abs/2606.07130, https://arxiv.org/abs/2606.28358, https://aclanthology.org/2026.bionlp-1.62.pdf, https://arxiv.org/abs/2607.00641, and https://arxiv.org/abs/2602.10995.

2026-07 Source-Usage Metric Provenance Update

The latest attribution and verification papers add a sharper constraint: showing a source-usage number is not enough unless the response also says which metric profile produced that number and what the number is allowed to mean. Do LLM Attribution Metrics Transfer? shows that attribution metrics do not reliably transfer across datasets or constructs, so a product should not present support or text_match as universal truth without exposing the metric method and validation scope. LLM-as-a-Verifier treats verifier design choices such as criteria decomposition, score granularity, and repeated scoring as part of the calibration surface. ProvenAI separates answer correctness, citation fidelity, and document influence, reinforcing that a clean source row is not proof of hidden model-internal reliance.

The service footer now renders metric provenance beside every source-usage number. Each visible source row carries usage_metric_profile, usage_metric_scope, support_metric_method, text_match_metric_method, weight_metric_method, and payout_metric_method, all hash-bound into the row and visible in source_footer.rendered_text. The response verifier publishes source_usage_metric_provenance_count and source_usage_metric_provenance_status, failing grounded display unless every visible source row exposes the expected profile, scope, and methods. The public source-footer verifier enforces the same gate for copied/exported footer artifacts. This keeps attribution auditable without implying that observable support/allocation metrics reveal the model's private computational reliance.

References: https://arxiv.org/abs/2606.23915, https://arxiv.org/abs/2607.05391, and https://arxiv.org/abs/2606.26449.

2026-07 Attribution-Gap Closure Update

Recent LLM-search attribution work separates source use from source credit. The attribution crisis in LLM search results defines the attribution gap as relevant content consumed by a search-enabled LLM minus sources credited in the output, and reports that deployed systems can cite fewer sources than they consume or emit citations that do not appear in the disclosed search trace. Cited but Not Verified adds the companion citation-quality problem: source links may resolve and look relevant while factual support remains much lower. Citation Grounding and CiteCheck show the same pattern in domain-specific settings by separating existence, relevance, metadata fidelity, and temporal validity from generic fluency.

The verifier now exposes attribution-gap closure as its own production display dimension. source_grounding_acceptance publishes attribution_gap_status, attribution_gap_verdict, accessed and credited source counts, and failure counters for consumed-without-credit, cited-without-access, and paid-hidden sources. Grounded display fails unless the attribution-gap verdict is closed and those failure counters are zero. This keeps payout attribution, source footer attribution, and source-access telemetry aligned before a ready response can imply that its sourcing is complete.

References: https://www.cambridge.org/core/journals/data-and-policy/article/attribution-crisis-in-llm-search-results-estimating-ecosystem-exploitation/170DD0B88E5F5AEA8F69F2E9AF1328E3, https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2606.00898, and https://arxiv.org/abs/2605.27700.

2026-07 Source-Identity Binding Update

Recent citation-hallucination papers make source identity a separate runtime failure mode. CiteCheck distinguishes exact citation matches from minor metadata corruption and major fabricated references, showing that a plausible reference must be grounded against external source metadata rather than trusted from its surface form. Phantom References uses a stricter identity-level definition of hallucinated citations: the referenced work must exist with compatible authorship. Detecting and Correcting Reference Hallucinations similarly treats URL validity as measurable and correctable, while Cited but Not Verified separates link accessibility, topical relevance, and factual support.

The service response verifier now binds every visible source row back to the event's source-reference metadata. source_grounding_acceptance publishes source_identity_count and source_identity_status; grounded display fails if a footer row's title, creator, work ID, chunk ID, URI, license, content hash, support/allocation metrics, evidence preview, or evidence span hashes diverge from the event source reference it claims to expose. This blocks a self-consistently rehashed footer from swapping a displayed URI or creator while leaving the private event trace unchanged.

References: https://arxiv.org/abs/2605.27700, https://arxiv.org/abs/2607.00738, https://arxiv.org/abs/2604.03173, and https://arxiv.org/abs/2605.06635.

2026-07 Temporal Grounding Disclosure Update

Recent temporal-RAG and public-information work adds another display failure class: a source can be real, correctly identified, and relevant while still being too stale for a current, latest, recent, or as-of claim. Freshness and the Limits of Heuristic Trend Detection in Temporal RAG shows that semantic similarity alone ignores time and can surface stale evidence for recency-sensitive queries. Citation Grounding includes citation temporality as a separate dimension from existence and relevance. Curated retrieval versus open web search in public AI information services frames currency and source trustworthiness as information-quality dimensions that remain invisible unless measured. When Benchmarks Age shows the same temporal-misalignment problem in factuality evaluation: static evidence can become wrong as the world changes.

The service verifier now exposes temporal_claim_markers, temporal_claim_marker_count, source_temporal_metadata_count, and temporal_grounding_status. Static answers pass without requiring temporal metadata. If the rendered answer uses temporal wording such as current, latest, recent, today, now, or as of, grounded display fails unless every visible source row carries temporal freshness metadata. This does not replace the full rdllm-source-freshness-audit/v1 artifact; it prevents the runtime response from implying freshness when the footer has no timestamped source basis to verify.

References: https://arxiv.org/abs/2509.19376, https://arxiv.org/abs/2606.00898, https://arxiv.org/abs/2607.05217, and https://arxiv.org/abs/2510.07238.

2026-07 Claim-Source Closure Update

Recent source-aware verification work adds a stricter failure class than unsupported citation: a claim can be supported somewhere while being attributed to the wrong visible source. ProvenanceGuard calls this cross-source conflation and evaluates source-aware factuality with per-claim source IDs, source-specific evidence routing, and attribution-swap probes. Citation-Closure Retrieval and Per-Rule Attribution makes a related point for regulated QA: systems need explicit claim-to-source closure rather than flattened, post-hoc source lists. Cited but Not Verified reinforces the same runtime rule by separating source accessibility, relevance, and factual support.

The service verifier therefore now treats claim-source closure as a production display gate. source_grounding_acceptance publishes claim_source_closure_count and claim_source_closure_status; every supported claim must bind to the visible source row whose label, work ID, and chunk ID match the claim row. A self-consistently rehashed footer that points a supported claim at a different work or chunk now fails before display, even if the evidence span itself remains syntactically valid.

References: https://arxiv.org/abs/2606.18037, https://arxiv.org/abs/2605.29742, and https://arxiv.org/abs/2605.06635.

2026-07 Source-Locator Integrity Update

Recent citation-reliability work separates source existence and accessibility from claim support. Cited but Not Verified evaluates source attribution across Link Works, Relevant Content, and Fact Check because factual support can remain weak even when links resolve. Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents finds that retrieval-enabled and deep-research systems still emit hallucinated or non-resolving URLs, and shows that URL health is measurable and correctable. CiteCheck makes a similar point for scholarly citations: verifying that the referenced work exists and is correctly specified complements claim-level verification.

The service verifier now treats visible source locators as their own production display dimension. source_grounding_acceptance publishes source_locator_count and source_locator_status; every visible source row must render its uri, deterministic verify handle, and content-hash prefix in the footer. This keeps a client from showing fact-support and payout metrics while hiding the locator information a user or auditor needs to check the source.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2604.03173, and https://arxiv.org/abs/2605.27700.

2026-07 Runtime Audit-Commit Update

The same recent work also changes the service audit boundary. A response is not production-ready merely because it can render claim-level source rows; the operator must later prove that the exact event, footer hash, display hash, source count, and audit-error state were durably committed before release. PaperTrail argues for user-facing claim-evidence provenance, CiteGuard and CiteCheck show that citation attribution needs retrieval-grounded and metadata-aware verification, and LLM-search attribution-gap measurements show that consumed sources and displayed citations can diverge in deployed systems. The Nature hallucination-incentives result also reinforces that systems need explicit abstention/fail-closed incentives rather than rewarding plausible answers that lack verifiable support.

The runtime therefore treats the hash-chained service audit log as part of the answer release gate. Readiness rejects corrupt existing audit chains, and attribution routes return a blocked response without answer, display, or source footer payload if the new audit entry cannot be committed. This keeps public source footers grounded in an operator-verifiable event history instead of becoming unprovable presentation text.

References: https://arxiv.org/abs/2602.21045, https://aclanthology.org/2026.acl-long.282/, https://arxiv.org/abs/2605.27700, https://www.cambridge.org/core/journals/data-and-policy/article/attribution-crisis-in-llm-search-results-estimating-ecosystem-exploitation/170DD0B88E5F5AEA8F69F2E9AF1328E3, and https://www.nature.com/articles/s41586-026-10549-w.

2026-07 Verification-Contract Update

The client verifier now publishes a standalone schema for rdllm-service-response-verification/v1, not only for the response payload. This is a product requirement, not a packaging detail: clients, launch gates, support bundles, and auditors need to validate the verifier result that says whether an answer/footer surface is displayable.

Recent work supports treating verifier outputs as first-class artifacts. Cited but Not Verified evaluates citation quality by separating URL accessibility, topical relevance, and factual support. CiteCheck separates retrieval from verification and emits structured comparison results for exact, minor, and major citation hallucinations. PaperTrail shows the value of claim-evidence provenance, while also showing that provenance detail must be usable enough to affect operator and user behavior. A Nature Communications medical-citation study found high rates of unsupported cited statements, which reinforces that a source-looking footer is not enough for display approval.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2605.27700, https://arxiv.org/abs/2602.21045, and https://www.nature.com/articles/s41467-025-58551-6.

The runtime now also fails closed on non-display-safe grounding. If the embedded grounding verdict is warning, failed, blocked_by_policy, or blocked_by_registry, the service response is blocked, includes a grounding_quality: audit error, and renders unsupported claim hashes in the footer. This follows the same recent evidence: citation systems can produce working links and plausible metadata while the cited source does not support the claim, so users need an explicit blocked status and unsupported-claim disclosure instead of a source-looking footer alone.

2026-07 Source-Grounded Acceptance Update

The verifier now exposes a nested rdllm-service-source-grounding-acceptance/v1 profile. This turns the research distinction between link presence, source relevance, factual support, and faithful citation into a machine-checkable product gate. A response can be internally consistent for audit while still failing grounded display acceptance; production display now requires visible verified source rows, supported claim evidence, minimum support score, non-escrow royalty-share coverage, and a rendered answer that includes the bound source footer.

This update follows three recent findings. Cited but Not Verified shows that high link validity and relevance do not imply factual citation correctness. How Do LLMs Cite? warns that inline citations can be produced by a distributed attribution heuristic rather than faithful source use. Citation-Closure Retrieval and Per-Rule Attribution shows that regulated workflows need claim-to-source closure, not post-hoc source lists. Indirect-prompt-injection benchmarks also reinforce that attribution must be evaluated end-to-end from ingestion through answer release.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2606.28358, https://arxiv.org/abs/2605.29742, and https://arxiv.org/abs/2601.10923.

2026-07 Launch-Gate Update

The operator surface now has a fail-closed launch gate because the newest citation and attribution papers keep separating visible citation shape from actual source support. Cited but Not Verified shows that working, relevant links can still fail factual support; Explicit Evidence Grounding via Structured Inline Citation Generation shows that document-level citation is easier than precise evidence-span grounding; How Do LLMs Cite? argues that inline citations may follow shallow attribution heuristics rather than faithful source use; Citation-Closure Retrieval and Per-Rule Attribution shows that regulated workflows need closure over all required rules, not just a plausible single source; and legal-citation hallucination benchmarks show that subtle misquotes and mismatches remain hard even for agentic verifiers.

The practical product rule is that an operator cannot rely on a clean README, a valid service config, or a source-looking footer in isolation. Before production display traffic, the deployment must jointly verify the profile controls, runtime service readiness, bootstrap manifest when present, and at least one saved attribution response footer. The launch gate is therefore a product decision surface, while the support bundle is the redacted artifact to share when the gate blocks.

References: https://arxiv.org/abs/2605.06635, https://arxiv.org/abs/2606.07130, https://arxiv.org/abs/2606.28358, https://arxiv.org/abs/2605.29742, and https://arxiv.org/abs/2606.21155.

2026-07 Source-Rationale Update

Recent citation-verification papers changed the mechanism target from "show a source and pay it" to "explain why this source is in the answer footer." The implementation now treats every visible footer row as a compact attribution claim: the row must name the source identity, claim-support path, source availability, reliance/licensing state, settlement state, and a stable source_rationale_hash. The rendered Markdown footer also carries a why=... reason code, and the rendered-attribution audit rejects source rows that do not explain source selection.

This update follows the recent evidence that citation-looking strings are not enough: source links can resolve without fact support, scholarly citations can have subtle metadata drift, and generative feature attribution needs an explicit contract for what is being explained. The practical rule is therefore fail closed: cite only rows with verified identity, support, availability, reliance, rights, and royalty/settlement coverage; otherwise downgrade the footer row to a review/escrow state.

Design Takeaways

  1. Cite every supported claim, not just the answer as a whole.
  2. Treat citation markers as constrained source pointers, not free-form text.
  3. Verify generated claims against cited evidence after generation.
  4. Keep retrieval, text matching, citation scoring, and training-data attribution as separate channels in the ledger.
  5. Show users a footer with source identity, evidence quote, source URI, content hash, evidence span hash, and grounding coverage.
  6. Hold value in escrow when no registered source can be traced.
  7. Enforce rights before attribution: a source can be retrievable but not licensed for generation, display, quote, external attribution, or training.
  8. Log span hashes and policy decisions because reproducible evidence identity can be weaker than document-level overlap.
  9. Treat conformance as a first-class product artifact. A provider should be able to prove that links, relevance, fact support, rights, receipts, and payouts agree.
  10. Separate source availability, source quality, citation integrity, and factual support. A working URL or registered source is not the same as evidence that supports a claim.
  11. Separate ownership proof from content matching. A hash can prove that two registrations point to the same text, but not which claimant is legally entitled to royalties; open conflicts should therefore escrow value until resolved.
  12. Make attribution portable. Receipts should not be trapped in one vendor's JSON API; they need credential-style proofs and provenance graphs that can move into wallets, registries, enterprise audit tools, and transparency services.
  13. Close the attribution gap explicitly. A source that was accessed, retrieved, or text-matched must be visible to the user, paid, or withheld with a reproducible rights/registry escrow reason.
  14. Separate public confidence from private audit. Users should see source and claim-support facts, while auditors can verify salted commitments for private prompts, evidence text, access traces, and economics.
  15. Bind provider telemetry to attribution receipts. A source footer is not enough if the provider can omit the retrieval/text-match trace; source-access spans, citation spans, and claim-support spans need shared hashes and portable verification.
  16. Treat probabilistic or model-internal attribution as evidence, not final truth. Token-level sensitivity, hidden-state probes, activation traces, and influence scores should be committed as auditable signals that can support, but not silently replace, runtime source and claim evidence.
  17. Make attribution configurable by stakeholder objective. Creator compensation, user confidence, publisher compliance, and platform auditability need different disclosure surfaces over the same signed event.
  18. Publish a provider-level attribution card. Per-answer receipts prove individual events; model buyers, regulators, creators, and platforms also need a signed, comparable deployment summary covering certification, source coverage, evidence channels, challenge handling, and known limitations.
  19. Publish the proof pack itself. Public confidence should not depend on a provider claiming that receipts, traces, statements, challenges, cards, summaries, and certification reports exist; the artifact set should have hash roots and inclusion proofs that independent verifiers can check.
  20. Make the user-facing answer verifiable. A source footer should have a companion answer provenance card that binds footer labels and claim span hashes back to the receipt and trace without exposing private prompt or evidence text.
  21. Materialize cited sources, not just citation strings. A grounded answer should carry a verifier report proving source hashes, quote hashes, claim evidence spans, source URIs, and answer-card bindings resolve to registered content without publishing private source text.
  22. Package the answer as a verifiable API object. Foundation-model adoption needs a response envelope that returns the rendered answer and embedded public proof artifacts together, so customers can verify the response boundary without private ledger access.
  23. Publish a provider integration profile. A foundation-model API needs a machine-readable contract for endpoints, response-envelope format, schemas, verifier commands, public surfaces, readiness checks, and bound proof hashes; otherwise attribution remains a custom integration instead of a deployable standard.
  24. Publish a well-known discovery manifest. Customers, creators, auditors, and downstream platforms need one stable entry point that tells them where the provider card, certification report, integration profile, response envelope, assurance bundle, schemas, verifier commands, and proof hashes live.
  25. Preserve derivative lineage. Foundation-model and agent pipelines increasingly use summaries, synthetic data, tool outputs, and transformed corpora; attribution must carry upstream work edges so derivative artifacts do not erase original owners from settlement.
  26. Benchmark provenance, not only payout. A provider should publish replayable attribution-quality evidence across clean, paraphrased, hard-decoy, escrow, and derivative-lineage cases so source finding is independently testable.
  27. Prove source influence, not just source presence. RAG attribution research now separates exposure, utility, and attribution, while counterfactual RAG papers test whether evidence changes decisions. Provider proof should therefore ablate credited sources and publish replayable influence margins.
  28. Treat consent as a lifecycle, not a one-time ingest flag. Rights reservations, opt-outs, and revocations need changed-policy hashes, preserved historical event hashes, and future-use denial probes so providers can prove they honor updated owner intent without rewriting past royalty records.
  29. Propagate consent changes across every attribution surface. A source can be correctly blocked at retrieval while still leaking through persistent memory, private reasoning, post-training signals, stale source footers, downstream exchange manifests, or settlement queues. The rights event therefore needs an SLA-bound propagation report over all those surfaces before future use or direct payout continues.
  30. Negotiate attribution before cross-provider use. Static proof publication is not enough when one AI system consumes another provider's answer or generated work; the caller needs a signed handshake that binds minimum level, required artifacts, source-footer relay, escrow relay, runtime headers, and downgrade rejection before the content enters a downstream workflow.
  31. Make attribution survive copying. Recent LLM-search work shows that relevant pages can be consumed without equivalent visible credit; therefore the answer itself needs a portable capsule binding the output hash, source-footer proof, federation handshake, C2PA-compatible assertion, and SCITT-like statement subject after it leaves the original product surface.
  32. Make footer confidence explicit. Recent citation-hallucination work shows that source-looking strings can be fabricated, stale, or weakly supportive, so the response should expose verified/warning/failed footer rows and a hallucination taxonomy grounded in source materialization and license proof.
  33. Bind the rendered footer itself. Recent verification work increasingly separates source identity, source support, confidence calibration, and human inspection, so the response should ship a signed client-rendering contract for the exact source rows and claim anchors users will see.
  34. Make private evidence challengeable. The public footer should not expose private prompts, evidence text, access traces, or payout accounts, but auditors still need a nonce-bound way to test whether redacted receipt paths open to the committed source, claim, rights, and royalty facts.
  35. Prevent attribution laundering after copy/reuse. Data-lineage and citation hallucination research both point to a second-hop problem: once an AI answer is copied into another workflow, downstream systems can cite only the wrapper or invent fresh citations. A portable report should bind the downstream event to the upstream capsule, verify the copied body hash, carry original source rows forward, and settle a pass-through pool to upstream owners.
  36. Clear obligations across providers. Data-valuation papers can estimate source influence, and citation-evaluation papers can test grounding, but a royalty market also needs a neutral clearing artifact that ingests provider statements and transitive reuse reports, deduplicates repeated submissions, holds overlapping evidence for review, and publishes payable/escrow totals.
  37. Bind attribution to payment instructions without overclaiming settlement. Once obligations are cleared, creators need remittance rows that can be reconciled by payment systems, but the attribution layer should not pretend a bank transfer has executed. Therefore the mechanism emits instruction-only rows with payout-account hashes, end-to-end IDs, remittance references, and hold preservation.
  38. Name attribution suppression explicitly. Recent attribution-bias work shows that a model can have source or authorship information and still omit visible attribution. RDLLM therefore treats footer omissions as an explicit attribution_suppression_count in answer cards and source-confidence reports, so a provider cannot hide known sources behind a generic citation failure.
  39. Require independent replay, not provider self-attestation. Recent citation and provenance work separates correctness, faithfulness, and support; RDLLM-L45 therefore turns the whole proof pack into a third-party audit attestation that binds public artifacts by hash, replays available verifiers, and records negative controls without publishing private prompts, source text, or payout accounts.
  40. Prove event revenue before payout. Attribution and clearing are not enough if the gross_revenue field is trusted input, so RDLLM-L46 adds revenue allocation reports that bind hashed subscription, advertising, API, enterprise, and marketplace revenue pools to event-level gross revenue and creator-pool totals before statements, clearing, and remittance.
  41. Prove the revenue pools themselves. A provider could conserve a fabricated pool, so RDLLM-L47 adds finance ledger attestations that reconcile hash-only invoice, billing, ad-server, API-meter, enterprise-contract, and marketplace exports to each revenue source without disclosing customer records.
  42. Publish the proof pack's replay order. A rich artifact set is not enough if auditors must infer verifier order by hand, so RDLLM-L48 adds proof dependency graphs that bind artifact hashes, separate hard replay dependencies from publication commitments, emit a topological replay order, and reject cycles.
  43. Monitor published proof surfaces after release. Attribution is only trustworthy if the provider card, certification report, response envelope, assurance bundle, and replay graph remain reproducible over time, so RDLLM-L49 adds an append-only publication monitor with Merkle snapshots, checkpoint history, artifact diffs, and certification-regression blocking.
  44. Bind proof artifacts to public trust roots. A witnessed checkpoint is still weak if verifier software does not know which provider, auditor, or witness keys are active or revoked, so RDLLM-L51 adds a trust registry for signer key hashes, key IDs, rotations, revocations, artifact signatures, and witness signatures.
  45. Make certification itself independently attestable. A certification report hash is useful, but adoption requires a signed object that a customer can verify without trusting the provider's web page. RDLLM-L52 adds certification attestations that bind the certification report hash, levels root, case-status root, certifier identity, target provider, and signature, then lets the trust registry verify the certifier key.
  46. Prove evidence sufficiency, not only source existence. Recent citation and evidence-ranking work shows that a valid source can still be redundant, ambiguous, or not the best support for a claim. RDLLM-L56 therefore ranks candidate spans per claim, requires the displayed span to be the top-ranked minimal sufficient evidence, and records a decoy margin before treating the footer as grounded.
  47. Adjudicate counterevidence before release. Citation verification and evidence ranking still allow one-sided answers when a claim has support but registered material directly disputes it. RDLLM-L57 therefore scans registered source spans for contradiction candidates and fails answers with unaddressed counterevidence before display or settlement.
  48. Close the release/application gap. A provider can publish correct late-stage grounding artifacts and still serve an answer envelope that does not depend on them. RDLLM-L58 therefore requires L55-L57 source availability, evidence sufficiency, and counterevidence reports to be embedded and bound in the response envelope before a high-certification release gate can emit.
  49. Close the answer-surface coverage gap. Sentence-level citation systems and claim-evidence interfaces still leave a serving risk: a provider can append an unsupported factual sentence to an otherwise grounded response. RDLLM-L59 therefore hashes every support-bearing public answer sentence and requires it to replay to a verified, sufficient, counterevidence-free claim row before release.
  50. Close the post-hoc citation gap. Retrieval-aware citation systems can still attach plausible sources after generation. RDLLM-L60 therefore binds every verified displayed claim to source-access spans and redacted generation-context block commitments captured before response delivery.
  51. Treat retrieved source text as evidence, not instructions. Recent prompt injection research shows that webpages, documents, and reusable prompts can carry machine-targeted instructions that alter model behavior. RDLLM-L61 therefore adds source boundary reports: each source packet must be hash-bound, role-labeled as evidence, excluded from control/instruction channels, and unable to modify attribution or payout policy.
  52. Prove which proof channels influenced the final answer. Recent attribution, citation, and prompt-injection work converges on the same operational gap: users need not only source footers, but a replayable reason why a source was cited, paid, or ignored. RDLLM-L62 therefore adds a decision provenance graph over claim grounding, visible footer rows, payout participation, and release decisions, with source text admitted as evidence only and never as payout or policy control.
  53. Calibrate attribution confidence instead of implying certainty. Recent RAG and faithfulness work shows that source correctness, actual reliance, and metric faithfulness can diverge. RDLLM-L63 therefore adds a calibrated attribution confidence report: every public claim, footer row, and payout-participation row carries a benchmark-backed lower confidence bound, and low-confidence rows must be disclosed or escrowed.
  54. Verify source authenticity before direct credit or payment. Recent poisoning work shows that retrieved knowledge bases can be adversarially injected, and source-attribution work shows that influence must be traced to the actual text responsible for a generation. RDLLM-L64 therefore binds public source rows to trusted origin evidence, archive consensus, active license terms, source-farm risk, poisoning risk, and synthetic-source disclosure; failed rows remain visible only with warnings and route payment to escrow until review.
  55. Make external verification economically accountable. Recent citation and provenance work motivates independent replay, but settlement systems also need consequences for incorrect or conflicted verifier attestations. RDLLM-L72 binds accepted verifier rows to trust-registry identity, non-revoked key hashes, slashable bond coverage, conflict disclosures, challenge rows, and slashing evidence before verifier-approved settlement can leave escrow.
  56. Make the economic usage log globally consistent, not merely signed. Certificate Transparency, SCITT, and witness systems show that inclusion proofs are not enough if different parties can be shown different roots. RDLLM-L73 therefore compares receipt-log snapshots across provider, creator, customer, and witness views, verifies append-only prefixes and required receipt inclusion, detects split-view roots, and escrows settlement when the usage log cannot be replayed as one consistent history.
  57. Make monitoring economically live. Transparency logs still fail in practice when nobody watches them, when monitors are incomplete, or when a provider can delay remediation after a public defect is discovered. RDLLM-L74 therefore requires registered independent watchtower attestations over the L73 subject, treats open or accepted public challenges as settlement blockers, and emits hash-only slashing and bounty rows for accepted verifier-observation failures.
  58. Prove that footer sources were actually relied on. Recent citation work shows that correct-looking references and source-support checks can still diverge from actual generation reliance. RDLLM-L100 therefore emits citation reliance receipts that bind visible footer rows 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 a directly settled source can be treated as faithful.
  59. Make license authorization transactional, not just declared. Machine-readable rights protocols and provenance ledgers are necessary but insufficient if the provider cannot prove the publisher or license server actually authorized the exact source access. RDLLM-L101 therefore emits license transaction receipts: signed authorization tokens, license-ledger inclusion, source-access nonce and meter binding, protocol-term matching, transaction validity checks, and escrow routing for missing, expired, unsigned, non-ledgered, or mismatched tokens.
  60. Make the answer footer the verification surface. Recent work separates source identity, factual support, actual reliance, confidence calibration, and rights authorization, so RDLLM-L102 emits grounded source footer receipts that bind each visible footer row to confidence, availability, exact public evidence regions, citation reliance, license transactions, and public verifier handles without exposing prompt, answer, source, evidence, or payout data.
  61. Make delivery part of attribution, not a UI convention. Faithful citations and grounded footer receipts still fail users if the served answer drops footer rows, span handles, or verifier metadata. RDLLM-L103 therefore emits source footer delivery receipts that bind the grounded footer to the proof-carrying response, copied output, gateway egress hash, source labels, claim span handles, and public verifier metadata.
  62. Make attribution portable as a minimum model API contract. Recent citation, provenance, and content-credential work points to the same deployment problem: a citation row is not trustworthy unless generic clients know which headers, embedded proof objects, verifier paths, and fail-closed policies must be present. RDLLM-L104 therefore emits foundation API attribution profiles that bind the provider card, certification report, integration profile, discovery manifest, response envelope, and L103 source-footer-delivery receipt into a vendor-neutral response contract.
  63. Make the relying client prove enforcement. API-boundary attestation work and content-provenance deployments show that provider metadata is insufficient if downstream clients can strip, ignore, or rewrite it. RDLLM-L105 therefore emits client attribution enforcement receipts that bind observed response headers, embedded proof objects, verifier commands, source labels, and the client's render/block decision before a chat, search, agent, or relay surface displays an attributed answer.
  64. Make persistent memory a provenance-bearing derived work. Long-running agents increasingly write summaries, profile facts, and cross-session memories; if those memory cells are later used in an answer, the user and creator need the same source carry-forward that a direct retrieval answer would have. RDLLM-L106 therefore emits persistent memory provenance receipts that bind memory writes, reads, source labels, upstream proof hashes, license and retention policy, royalty obligations, delete tombstones, and visible footer labels.
  65. Make private reasoning attribution auditable without exposing chain-of-thought. Foundation models, routers, and agent runtimes increasingly use hidden scratchpads, delegated reviewers, and intermediate summaries. RDLLM-L107 emits private reasoning attribution receipts that commit to those private traces by hash, bind them to L106 memory and L105 client proofs, require every hidden source label to appear in the verified footer, and preserve royalty rows without publishing raw reasoning text.
  66. Prevent synthetic-source attribution laundering. Recent source-attribution and cited-RAG work shows that a visible source can be relevant, reachable, and cited while still being an AI-generated wrapper or weakly supported proxy for the original human work. RDLLM-L121 therefore adds source-origin lineage: direct payout requires trusted human-origin attestation; synthetic sources require upstream creator lineage and share conservation; unknown or unattributed synthetic sources are shown to users but settled to origin-review escrow.
  67. Make the footer human-inspectable without exposing full source text. Recent citation-auditing work emphasizes that users over-trust bare citations and need visible evidence that the source actually supports the answer. RDLLM-L122 therefore adds evidence-preview footers: each verified visible claim must publish a short permissioned snippet, source URL, warrant label, origin label, and proof hash, while full source text, prompts, answers, private reasoning, and payment data remain undisclosed.
  68. Make the source preview click-through verifiable. Recent citation-verification and source-auditing work shows that link labels and snippets are still weak unless the reader can resolve the exact passage that grounded the claim. RDLLM-L123 therefore adds evidence-locator manifests: each preview snippet must bind to an exact public resolver URL, resolver status, and snapshot or text-fragment proof without redisclosing full source or excerpt text.
  69. Make foundation-model attribution provider-neutral. Current model APIs expose different native response envelopes, tool-call shapes, citation annotations, streaming events, and metadata surfaces. RDLLM-L125 therefore adds a composite foundation adapter: OpenAI Responses, Anthropic Messages, Google Gemini, Meta/Llama-style, Mistral, Cohere, xAI, Bedrock, Azure OpenAI, and OpenAI-compatible responses must bind their native output hash, headers, JSON proof fields, citation/tool paths, and final streaming metadata to the same RDLLM response envelope, source-footer delivery, and citation URL-health receipts before a client can call the answer grounded.
  70. Make provider compatibility fixture-backed. RDLLM-L126 adds a foundation provider conformance matrix so every supported provider family publishes hash-only positive and negative fixtures for attribution-critical response modes, claim-support footers, parametric-memory fallback, and fail-closed citation or proof failures.
  71. Make provider compatibility executable at response time. RDLLM-L127 adds a foundation runtime adapter receipt so a concrete native provider response either normalizes into the RDLLM response envelope, footer, URL-health proof, attribution headers, JSON proof fields, citation paths, and stream-final hashes, or fails closed before display.
  72. Make multi-provider routing non-bypassable. RDLLM-L128 adds a foundation runtime router receipt so broker APIs, fallback stacks, latency routers, and cost routers must prove every candidate provider route is adapter-backed, conformance-backed, hash-committed, and fail-closed before any selected provider response is displayed.
  73. Make backend model substitution non-bypassable. RDLLM-L129 adds a foundation model deployment attestation so the selected route must bind to an active provider deployment key, signed model/version commitments, and request/response boundary hashes before display.
  74. Make composite answers non-bypassable. RDLLM-L130 adds a universal composition receipt so an answer assembled from multiple foundation providers must bind every segment to one released L129 deployment attestation, source-footer delivery hash, telemetry span commitment, and conserved provider weight.
  75. Make source-grounded composition settleable. RDLLM-L131 adds a universal composition settlement receipt so every L130 provider segment must bind its displayed source labels and claim IDs to source-entitlement weights, creator-obligation rows, preserved source-footer delivery, and conserved revenue allocation totals. Payable rows require licensed or verified sources; unresolved rows go to escrow, and disputed, blocked, or revoked rows are held.
  76. Make foundation-model adoption one contract, not a provider-by-provider assertion. RDLLM-L132 adds a universal foundation model contract so all supported provider families must share the same adapter, conformance, runtime, router, deployment, composition, settlement, discovery, and public surface proof chain before a response can be released as RDLLM verified.
  77. Make native provider calls pass through an attribution gate before invocation. RDLLM-L133 adds a universal invocation guard so a raw OpenAI-, Anthropic-, Gemini-, Bedrock-, Azure-, xAI-, Cohere-, Mistral-, Meta/Llama-, or OpenAI-compatible call cannot bypass the L132 contract, selected route, deployment attestation, request/response boundary, source-footer requirement, fail-closed headers, or GenAI telemetry.
  78. Make deployment-wide provider usage reconcile to the gate. RDLLM-L134 adds a universal invocation coverage report so every native provider meter event must match one L133 guard, gateway egress record, source-footer delivery hash, response-envelope hash, billed unit row, gross-revenue row, creator-pool row, and provider invoice row before complete attribution coverage can be certified.
  79. Make coverage non-repudiable. RDLLM-L135 adds a universal invocation witness report so every L134-covered native provider call must bind to a provider-signed usage receipt, independently observed egress event, and independent witness quorum before a deployment can claim omitted calls would be externally detectable.
  80. Make exported content carry attribution after it leaves the chat surface. RDLLM-L136 adds a universal content credential that binds output hashes, source-footer delivery, response envelopes, invocation witnesses, and C2PA/VC-shaped provenance assertions so copied text, media, files, and agent handoffs can still point back to their attribution proof chain.
  81. Make deployment adoption inspectable as one public passport. RDLLM-L137 adds a universal RDLLM passport that binds certification, provider card, integration profile, discovery manifest, assurance bundle, proof graph, foundation adapters, invocation controls, composition/settlement receipts, and content credentials into a single offline-verifiable provider object.
  82. Make adoption provider-neutral and procurement-ready. RDLLM-L138 adds a universal adoption standard package with required artifacts, implementer roles, SDK surfaces, public discovery surfaces, verifier commands, procurement gates, and standards mappings, so a foundation-model provider, gateway, enterprise client, auditor, registry, or clearinghouse can adopt the same attribution mechanism without private integration rules.
  83. Make adoption executable before compatibility claims. RDLLM-L139 adds a universal interop test kit with provider-family golden fixtures, SDK bindings, CI/offline runners, negative mutation cases, verifier commands, and discovery paths, so a provider, gateway, SDK, client, or auditor can replay compatibility instead of trusting an implementation declaration.
  84. Make runtime context access become attributable evidence before the answer is released. RDLLM-L140 adds a universal context provenance bridge for MCP tools, retrieval, vector stores, file search, browser search, enterprise connectors, creator license endpoints, memory, and media credentials. Every context event must be authorized, licensed, projected into a source claim, rendered in the footer when it supports the answer, bound to agent-step attribution, and projected into royalty settlement. Unauthorized context, stale leases, hallucinated citations, missing footers, unbound agent steps, rights-denied sources, token-audience mismatches, connector audit gaps, and private text leaks fail closed.
  85. Make displayed citations independently verifiable before users rely on them. RDLLM-L141 adds a universal citation verification contract that binds the L140 context bridge to source identity, resolver/URL health, exact evidence locators, metadata fidelity, claim support, evidence-force calibration, source confidence, warranted footer rows, rendered attribution audits, source authenticity, and royalty state. Nonexistent sources, metadata drift, inaccessible locators, unsupported cited claims, overclaimed evidence force, footer/context mismatches, hallucinated labels, missing royalty state, stale snapshots, and private-text leaks fail closed.
  86. Treat cached or reused answers as fresh attributable usage, not as free provider-side bypasses. RDLLM-L142 adds a universal grounded reuse contract for semantic answer caches, gateway response caches, native provider prompt/KV caches, reusable agent reports, and enterprise RAG caches. It requires query-equivalence and evidence-overlap checks, source freshness, consent/license continuity, L141 citation continuity, cache-collision resistance, provider-family coverage, and a new royalty-metered reuse event before a cache hit can be displayed as grounded.
  87. Cover every declared model capability, not just text responses. Recent citation-integrity work shows that a source-looking footer can be fabricated, unsupported, stale, or metadata-drifted, while current model APIs expose attribution-relevant behavior across tools, web search, files, vision, audio, realtime sessions, image/video generation, embeddings, reranking, fine-tuning, batch, safety, and local-runtime surfaces. RDLLM-L181 therefore makes every declared capability and modality pair prove either verified source-footer behavior or an explicit no-source abstention path, with settlement held and invocation blocked for uncovered capability rows.

2 June 2026 Verification Addendum

The L130 implementation pass rechecked the most relevant recent primary sources for the production bypass case: a model gateway, broker API, or fallback stack can strip attribution even if one upstream provider response was correctly grounded. The update maps those sources into a concrete invariant: attribution cannot be a single-provider response feature; it must be enforced by the router that chooses the model actually displayed to the user. The L129 pass extends the same evidence boundary from the router to the selected backend deployment: a route label is not enough unless the provider signs the model deployment identity and binds it to the concrete request/response boundary. The L131 pass extends the boundary from attribution proof to settlement proof: showing a source footer is not enough unless the same source rows, claim IDs, and provider segment weights reconcile to payable, escrowed, or held creator obligations under a conserved revenue allocation pool. The L132 pass turns L125-L131 into a single adoption contract: provider families with different native APIs can only claim RDLLM compatibility when they publish one reproducible proof chain that covers provider discovery, public surfaces, runtime route selection, deployment identity, source footer, and settlement readiness. The L133 pass moves that contract from publication to pre-call enforcement: the gateway must prove the exact native invocation carries the L132 hash, route hash, deployment hash, request-projection hash, response-binding hash, source-footer delivery hash, response-envelope hash, fail-closed header contract, and provider/model telemetry before it calls the model. The L134 pass moves enforcement from a single invocation to a deployment window: native provider meters, gateway egress logs, L133 guard receipts, source-footer delivery hashes, response-envelope hashes, invoice rows, gross revenue, and creator-pool rows must reconcile one-to-one, or the deployment cannot claim that all foundation-model usage is attributable and settlement-ready. The L135 pass adds non-repudiation to that window: provider-signed usage receipts, independent egress observations, and independent witness quorum evidence must bind to each covered invocation, or the deployment cannot claim omitted foundation-model calls are externally detectable. The L136 pass makes source attribution survive export and copying: the generated asset itself carries a credential-style proof pointer to the answer envelope, source-footer delivery, invocation witness, and upstream proof chain. The L137 pass makes provider adoption inspectable: every proof artifact needed to evaluate a deployment is bound into one passport with public surfaces and verifier commands. The L138 pass turns that passport into an implementer-facing standard: the package names the required artifacts, roles, SDK surfaces, procurement gates, discovery paths, and standards mappings needed for universal adoption across foundation model providers, gateways, enterprise clients, creator registries, auditors, and clearinghouses. The L139 pass turns the standard into an executable compatibility kit: provider families must ship golden request/response fixtures, SDKs must prove fail-closed footer/proof handling, CI and offline runners must replay the kit, and negative mutation cases must block before a deployment claims universal RDLLM adoption.

May 2026 Literature and Standards Scan

The latest improvement pass focused on sources that directly affect attribution quality, training-data provenance, and privacy-preserving proof:

Late-2025 to May-2026 Attribution Scan

This pass focused on papers and standards that affect the exact question the mechanism must prove: not only who should be paid, but which source material the model relied on, whether the visible citation is faithful, and whether retrieved source text was safely treated as data.

Papers and Relevance

Standards and Policy Signals

Implementation Changes Made