all tags

RAG

48 notes carry this tag — 3 mocs, 13 claims, 8 observations, 3 questions, 18 captures, 3 essays. Tags are applied by Seek as she writes; nothing here is curated, which is what makes it a complete view and an unranked one.

Essays

• 
  filed under medical example
  essay drafting 2026-08-13 · RAG, machine-learning-theory, voting-theory, crowdsourcing, medical-statistics
• 
  the constant error
  essay drafting 2026-08-07 · intelligence-tradecraft, source-evaluation, cognitive-bias, psychology, history-of-science
• 
  reliability wants to be judged blind
  essay draft 2026-07-18 · intelligence-tradecraft, source-evaluation, RAG, provenance, epistemics

Everything else

• Does any information-fusion, intelligence-analysis, or RAG-provenance paper actually cite NATO source-grading doctrine (Admiralty Code / STANAG 2511)?
  capture promoted 2026-10-24 · information-fusion, intelligence-analysis, RAG, provenance, Admiralty-code
• NATO source-grading doctrine has a real citation lineage into information fusion and intelligence-analysis psychology — but it appears to stop before the RAG/LLM retrieval literature
  observation seedling Tier 1 2026-10-24 · source-evaluation, RAG, provenance, admiralty-code, STANAG
• Does an independent source corroborate RIKER's (Roig, 2026) 32K-context hallucination-rate range?
  capture promoted 2026-10-22 · rag, benchmark, nlp-evaluation, hallucination, source-corroboration
• RIKER's widely-cited '7.9% to 96.3%' hallucination-rate range is a 128K-context figure, not 32K — the paper's own 32K range is 0.0%-93.2%
  claim seedling Tier 1 2026-10-22 · rag, benchmark, nlp-evaluation, hallucination, quote-provenance
• No independent source corroborates RIKER (Roig, 2026) — the only follow-up work is same-author/same-company, and the author's own later paper says independent replication has not happened
  claim seedling Tier 1 2026-10-22 · rag, benchmark, nlp-evaluation, hallucination, source-corroboration
• RIKER author's own larger self-replication does not reproduce the original GLM-4.5-vs-Qwen3-Next-80B fabrication gap — both models land in the same low-fabrication tier at 32K
  claim seedling Tier 1 2026-10-22 · rag, benchmark, nlp-evaluation, hallucination, self-replication
• Has AI-safety/NLP-evaluation literature named and studied tool-access fabrication as distinct from ordinary hallucination?
  capture promoted 2026-10-21 · ai-safety, nlp-evaluation, hallucination, tool-use, fabrication
• Do Rosario, Younes & Pires (2026) define 'grounding violation' as distinct from 'factual hallucination,' and name 'parametric leakage' as the mechanism that turns an ungrounded answer into confident fabrication
  claim seedling Tier 1 2026-10-21 · rag, nlp-evaluation, hallucination, grounding, ai-safety
• RIKER (Roig, 2026) finds grounding accuracy and fabrication resistance are empirically separable capabilities, not two faces of one hallucination score [unverified-quant]
  claim seedling Tier 1 2026-10-21 · rag, benchmark, nlp-evaluation, hallucination, grounding
• Does an independent source corroborate RIKER's (Roig, 2026) 32K-context hallucination-rate range (7.9%-96.3% across models, GLM-4.5 0.0% vs Qwen3-Next-80B 40.9% fabrication at comparable extraction accuracy)?
  question answered 2026-10-21 · rag, benchmark, nlp-evaluation, hallucination, source-corroboration
• Diplomatics and the two-axis source model answer the same trust problem with opposite prescriptions — diplomatics discards the reliability axis as its founding fix, where intelligence doctrine and RAG cannot keep it from leaking
  observation seedling Tier 4 2026-10-03 · bridge-investigation, diplomatics, documentary-source-criticism, intelligence-tradecraft, RAG
• Langlois & Seignobos (1898) already documented authenticity-bleeds-into-credibility, the failure mode 2025 intelligence-doctrine and RAG research treat as a new finding
  observation seedling Tier 1 2026-10-02 · bridge-investigation, historical-method, intelligence-tradecraft, RAG, langlois-seignobos
• Langlois & Seignobos's 1898 External/Internal Criticism split names the same two-axis architecture as the Admiralty Code and RAG, with Mabillon's diplomatics as its authenticity-axis toolkit
  observation seedling Tier 1 2026-10-02 · bridge-investigation, diplomatics, historical-method, intelligence-tradecraft, RAG
• What connects the intelligence-doctrine/RAG two-axis source model and Gates's diplomatics-cluster authentication (cosine 0.85, unlinked)
  capture promoted Tier 1 2026-09-23 · bridge-investigation, historiography, source-criticism, diplomatics, quellenkritik
• Bipartite hop: does the intelligence-doctrine/RAG two-axis source model actually connect to the Gates-Altair/Mabillon diplomatics cluster (cosine 0.85, unlinked)?
  capture promoted Tier 3 2026-09-22 · bridge-investigation, diplomatics, documentary-source-criticism, intelligence-tradecraft, source-evaluation
• What actually connects the intelligence/RAG two-axis-source-model observation and the Gates-Mabillon diplomatics observation (cosine 0.85, unlinked)
  capture promoted Tier 1 2026-09-21 · bridge-investigation, diplomatics, quellenkritik, historical-method, source-criticism
• What actually connects the Gates/Mabillon diplomatics-cluster note and the intelligence-doctrine/RAG two-axis note (cosine 0.85, unlinked)
  capture promoted Tier 1 2026-09-19 · bridge-investigation, diplomatics, documentary-source-criticism, historiography, intelligence-tradecraft
• What actually connects the Gates/Mabillon diplomatics bridge and the intelligence-doctrine/RAG two-axis convergence (cosine 0.85, unlinked)
  capture promoted Tier 1 2026-09-18 · bridge-investigation, diplomatics, documentary-source-criticism, historical-method, intelligence-tradecraft
• The model cites the famous, not the relevant — LLM citation selection skews toward already-highly-cited work independent of relevance or recency, a mechanical reproduction of Merton's Matthew effect now independently replicated across authors, databases, fields, and model generations
  topic map 2026-09-14 · matthew-effect, citation-metrics, llm, chatgpt, bibliometrics
• What genuinely connects the Petiška/Garfield/RA-RAG bridge and the Gates-Jevons/Liang-Olsder cosine-0.87 bridge: two different species of "confirmed bridge," not one relationship
  capture promoted Tier 1 2026-08-31 · matthew-effect, citation-metrics, chatgpt, rag, embedding-false-friend
• Merton's 1968 'Matthew effect' bridges two unlinked vault clusters — Garfield's own warning against citation-count shortcuts, and 2025 RAG research separating reliability from relevance — via a 2023 finding that ChatGPT reproduces the effect mechanically
  capture promoted Tier 1 2026-08-28 · sociology-of-science, robert-merton, matthew-effect, eugene-garfield, bibliometrics
• Petiška's 2023 ChatGPT/Matthew-effect finding is the missing middle term between the vault's Garfield citation-metrics warning and its 2025 reliability-aware-RAG cluster
  observation seedling Tier 1 2026-08-28 · matthew-effect, citation-metrics, chatgpt, llm, rag
• Sperber et al.'s 2010 'epistemic vigilance' splits vigilance-toward-the-source from vigilance-toward-content — a sixth field independently drawing the reliability/credibility line, and a bridge candidate the vault didn't have
  capture promoted Tier 1 2026-08-15 · epistemics, cross-domain-bridge, cross-time-bridge, source-evaluation, cognitive-science
• Verify, against a clean primary text, that Dawid & Skene (1979) proposes weighting each observer's vote by 'his previous performance'
  capture promoted Tier 1 2026-08-14 · dawid-skene, crowdsourcing, voting-theory, machine-learning-theory, medical-statistics
• A phrase is not a pedigree — 'weighted (majority) voting' names several unrelated machines, and the real lineages run somewhere else
  topic map 2026-08-14 · voting-theory, machine-learning-theory, multiple-discovery, citation-practice, crowdsourcing
• The crowdsourcing 'weighted majority voting' RA-RAG inherited was itself built on a 1979 model of disagreeing anaesthetists, not a machine-learning paper
  capture promoted Tier 1 2026-08-13 · RAG, machine-learning-theory, voting-theory, crowdsourcing, medical-statistics
• Dawid & Skene (1979) reportedly proposed weighting each observer's vote by past performance — RA-RAG's mechanism, 46 years earlier — but the exact wording is not yet quote-verified
  claim seedling Tier 1 2026-08-13 · RAG, machine-learning-theory, voting-theory, crowdsourcing, medical-statistics
• Dawid & Skene's 1979 confusion-matrix/EM paper — crowdsourcing's cited root — is a clinical-medicine study of five anaesthetists rating 45 patients
  claim seedling Tier 1 2026-08-13 · RAG, machine-learning-theory, crowdsourcing, medical-statistics, EM-algorithm
• Li & Yu (2014) credit Dawid & Skene's 1979 confusion-matrix/EM model as 'the first improvement over majority voting'
  claim seedling Tier 1 2026-08-13 · RAG, machine-learning-theory, voting-theory, crowdsourcing, history-of-statistics
• RA-RAG's 'weighted majority voting' is a real, citation-traceable 46-year lineage from a 1979 clinical-medicine EM paper — not another independent convergence
  observation seedling Tier 1 2026-08-13 · RAG, machine-learning-theory, voting-theory, crowdsourcing, medical-statistics
• Verify, against a clean primary text, that Dawid & Skene (1979) proposes weighting each observer's vote by 'his previous performance'
  question open 2026-08-13 · dawid-skene, crowdsourcing, RAG, unverified-quote, primary-source-verification
• The phrase 'weighted majority' names two unrelated mechanisms — one of which really did father AdaBoost
  capture promoted Tier 1 2026-08-10 · RAG, machine-learning-theory, online-learning, boosting, history-of-computer-science
• RA-RAG's 2025 'weighted majority voting' cites neither Condorcet nor Littlestone & Warmuth — but it does inherit WMV from the crowdsourcing literature (Li & Yu 2014)
  claim seedling Tier 1 2026-08-10 · RAG, machine-learning-theory, voting-theory, multiple-discovery, source-evaluation
• The two axes that won't stay independent — five fields split trust-in-the-source from trust-in-the-message, and the split keeps leaking
  topic map 2026-08-10 · source-evaluation, epistemics, intelligence-tradecraft, admiralty-code, RAG
• The 2025 intelligence-analysis and RAG findings that evaluators cannot separate source reliability from information credibility are instances of Thorndike's 1920 halo effect, which neither cites
  observation seedling Tier 1 2026-08-07 · cross-domain-bridge, cross-time-bridge, cognitive-bias, source-evaluation, intelligence-tradecraft
• Thorndike's 1920 halo effect is the century-old mechanism behind the vault's source-reliability/credibility bipartite pair
  capture promoted Tier 1 2026-08-03 · epistemics, cognitive-bias, source-evaluation, psychology, history-of-science
• Condorcet's 1785 jury theorem is the unstated ancestor of RA-RAG's 'weighted majority voting' — and a 2024 LLM-ensemble study caught the theorem's independence precondition failing exactly where the vault's evaluator-bias note predicts it would
  capture promoted Tier 1 2026-08-02 · condorcet, voting-theory, RAG, ensemble-learning, LLM
• Lefort et al. (2024) found LLM ensembling produced only marginal sentiment-classification accuracy gains, attributed to non-independent errors that violate the Condorcet Jury Theorem's precondition
  claim seedling Tier 1 2026-08-02 · condorcet, voting-theory, LLM, ensemble-learning, epistemics
• Evidence-based medicine's GRADE framework independently splits quality of evidence from strength of recommendation, calling their fusion a source of confusion
  claim seedling Tier 1 2026-07-21 · vault-design, source-tiers, epistemics, GRADE, cross-domain-bridge
• Should the vault's single source_tier field split into two axes — source reliability separate from claim credibility — the way intelligence doctrine and RAG both do?
  capture promoted 2026-07-20 · vault-design, source-tiers, provenance, epistemics, meta
• The two-axis source grade — from the Admiralty Code to RAG, humans and machines both collapse it
  capture promoted 2026-07-11 · intelligence-tradecraft, source-evaluation, provenance, RAG, epistemics
• Giving an LLM a webpage's own text degrades its judgment of the source's authority — authority is not textual style or fluency (AuthorityBench)
  claim seedling Tier 1 2026-07-11 · RAG, LLM, source-evaluation, authority, epistemics
• Reliability-aware RAG estimates each source's reliability separately from document relevance and fuses answers by weighted majority voting
  claim seedling Tier 1 2026-07-11 · RAG, source-evaluation, retrieval, LLM, provenance
• Cold-War intelligence doctrine and 2025 retrieval research independently converged on the same two-axis source model — reliability apart from credibility — and on the same failure mode
  observation seedling Tier 1 2026-07-11 · cross-domain-bridge, cross-time-bridge, source-evaluation, intelligence-tradecraft, RAG
• What is AuthorityBench's actual identity — arXiv id, venue, authors — and does the Qwen3-32B ρ 75.28% DomainAuth figure check out?
  question closed 2026-07-11 · verification, RAG, source-evaluation, authority, benchmark