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Paper Citation Record · LEDGER

Unfamiliar Finetuning Examples Control How Language Models Hallucinate

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2403.05612.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2403.05612 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:31:59.831137Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e847c900-f1ff-4b67-adb6-c42e79d94777 · inbound

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation cites this paper.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.831137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.831137Z digest=sha256:25a91f3839ed58970d4778e59a25b3c9fd20405fa15d67da16100ed90908352b

Observation a4d88254-f59d-4bdf-9567-2c37e02615fb · inbound

Stochastic Chameleons: Irrelevant Context Hallucinations Reveal Class-Based (Mis)Generalization in LLMs cites this paper.

Stochastic Chameleons: Irrelevant Context Hallucinations Reveal Class-Based (Mis)Generalization in LLMs Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:09:21.817408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:09:21.817408Z digest=sha256:690a34e86c48a4b4af096f0ff65a2066b5be35503151ba0f2a73479f1f015bdd

Observation 56330a92-4448-4380-902d-20dc3f7de3cc · inbound

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models cites this paper.

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T20:03:46.944390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:03:46.944390Z digest=sha256:578182a12e4bb5d752df05fbf5bcf09d267b92ca32d458e460c7731aee28f83b

Observation 147b40e4-a6ea-4bea-9aca-dc29525df415 · inbound

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation cites this paper.

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T21:47:57.886166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:47:57.886166Z digest=sha256:143a976c9559a417925afc557e0f551cb81466ddadeea89b516450aa88d27478

Observation d15bf24f-e233-40de-ae03-f749b7432737 · inbound

Learning Facts at Scale with Active Reading cites this paper.

Learning Facts at Scale with Active Reading Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T21:05:45.219566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:05:45.219566Z digest=sha256:814545a9548518f0ba37170c437192ae09b157be663f861810001fea923e5991

Observation cb943ee2-cf26-40a3-b4b8-b7879a812195 · inbound

Connections between reinforcement learning with feedback,test-time scaling, and diffusion guidance: An anthology cites this paper.

Connections between reinforcement learning with feedback,test-time scaling, and diffusion guidance: An anthology Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T10:22:38.275970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:38.275970Z digest=sha256:d9e057c37d0648633b0a6a7a32107da8cd426519dab1ceec21a80e680f513530

Observation 694d0a83-ec5c-4e89-8a23-614bfa011c49 · inbound

Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation cites this paper.

Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:25:35.037430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-18T01:23:01.921132Z digest=sha256:dfd0035becfcf61ff474197cd2700e089e757e10028d139fbe455512128ff5b2

Observation f509c9fb-bb4d-47fb-a64f-03041e99ee1a · inbound

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs cites this paper.

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:41:21.362760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-22T09:38:04.387777Z digest=sha256:1487c45e56ecf826f93c384cbf8249d36d380af82e168922174e00adb010f254