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Paper Citation Record · LEDGER

A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 41 inbound Pith citation observations for arXiv:2307.03987.

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

pith.paper-citation-record.v1
2307.03987 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 41 of 41 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 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:56:19.292160Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:26:46.313156Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3136accc-1009-4935-8a90-0d000218a97b · inbound

A Survey of Hallucination in Large Foundation Models cites this paper.

A Survey of Hallucination in Large Foundation Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 144

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arxiv_id, observed 2026-05-16T15:21:00.990074Z

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=2026-05-16T15:21:00.778049Z digest=sha256:6f3e56fa0431927b726c48751aced97849bea6b2e9e670ef7c1deaa566c0a776

Observation fdde8df5-7a3c-4133-ac82-faccc90ba7f2 · inbound

Chain-of-Verification Reduces Hallucination in Large Language Models cites this paper.

Chain-of-Verification Reduces Hallucination in Large Language Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 115

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verified exact
arxiv_id, observed 2026-05-18T01:06:50.493171Z

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=2026-05-18T01:06:49.811982Z digest=sha256:a39174313bcd61c1b23eba94372eb6ce79a487b823b12de1e8d574315e3af1d3

Observation 8c4ad1b5-fc5f-4e75-87aa-f1ddd654bc78 · inbound

Capabilities of Gemini Models in Medicine cites this paper.

Capabilities of Gemini Models in Medicine A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 273

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arxiv_id, observed 2026-05-15T17:13:22.983347Z

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=2026-05-15T17:13:22.759147Z digest=sha256:c3b79be50cce8c178aeca947cb9941d1566a311b2e83ca379913d72cbba302fd

Observation 503a75f1-a22e-4e28-84ed-6f9055076d36 · inbound

Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs cites this paper.

Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 75

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metadata mismatch
arxiv_id, observed 2026-05-18T00:52:02.585126Z

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=pdf_text observed=2026-05-18T00:52:02.421389Z digest=sha256:c8a1f2f25c338781b970833971f754d25bb58b1608992e21ba0733033942b9f9

Observation 88751f27-914b-45a6-b844-8e0593ccc66e · inbound

Hallucination Detection: A Probabilistic Framework Using Embeddings Distance Analysis cites this paper.

Hallucination Detection: A Probabilistic Framework Using Embeddings Distance Analysis A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 2499

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no resolver link, observed 2026-08-08T15:56:19.292160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:56:19.292160Z digest=sha256:dadc7bde4442a3fde86c38e686d924244742b46caf5bc66f5b485e235821fb5a

Observation d0023a21-8acd-47d3-b166-c19564f096e2 · inbound

Pierce the Mists, Greet the Sky: Decipher Knowledge Overshadowing via Knowledge Circuit Analysis cites this paper.

Pierce the Mists, Greet the Sky: Decipher Knowledge Overshadowing via Knowledge Circuit Analysis A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 45

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no resolver link, observed 2026-08-07T15:39:19.716465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:39:19.716465Z digest=sha256:7eae983e8650976b7714c32833fcb9d482bba7017694a53aa0b878f615db6402

Observation 4d097906-9770-4947-ace2-7f27f0df66dd · inbound

BugRepro: Enhancing Android Bug Reproduction with Domain-Specific Knowledge Integration cites this paper.

BugRepro: Enhancing Android Bug Reproduction with Domain-Specific Knowledge Integration A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 47

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no resolver link, observed 2026-08-07T15:36:11.325010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:11.325010Z digest=sha256:e7da617f63fb60ee040715d9af2ce952bab43b112d43aa0f77902c31a6b4bb2e

Observation 8039a8ae-697e-4f25-a377-2c03fda0398e · inbound

Paying Alignment Tax with Contrastive Learning cites this paper.

Paying Alignment Tax with Contrastive Learning A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 27

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no resolver link, observed 2026-08-07T14:20:39.991654Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:20:39.991654Z digest=sha256:5a5487cad6c9bbe2bc4d760ffe27e35a3eb49b36d5eba449ba293cd83bb656a4

Observation 26768f06-daa1-4702-855e-285954bf1842 · inbound

Maximizing Confidence Alone Improves Reasoning cites this paper.

Maximizing Confidence Alone Improves Reasoning A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 47

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no resolver link, observed 2026-08-07T13:07:50.421957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:07:50.421957Z digest=sha256:e0ba6db59d6941db111025c950f3b105b6b13a6b4d875881d62e49fffeb5c9ee

Observation 5c76f4cd-e27e-4b94-9efa-e569534d6627 · inbound

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation cites this paper.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 17

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no resolver link, observed 2026-08-07T05:05:59.420504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:05:59.420504Z digest=sha256:664365f88fdd6eea866a26165c32bde23ba36625d451e1beeecba76dadd0084d

Observation 28f2a9ca-d877-4bb2-9f0d-ad3a747c8606 · inbound

MALM: A Multi-Information Adapter for Large Language Models to Mitigate Hallucination cites this paper.

MALM: A Multi-Information Adapter for Large Language Models to Mitigate Hallucination A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 38

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no resolver link, observed 2026-08-07T00:55:58.782316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:55:58.782316Z digest=sha256:60ba61d1cd07cb4fe146c9d9902a2991a547c9cea8ffbbdf8a7bc8a7bf5c10f7

Observation 4e99e11f-e55e-4aa3-80d5-5f162e0ee8da · inbound

Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks cites this paper.

Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 28

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arxiv_id, observed 2026-05-19T09:52:14.126420Z

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=pdf_text observed=2026-05-19T09:48:56.990745Z digest=sha256:dcde598cc49a5d5786b9aeed4ab347dc169527f03027af14d78fa4f230ede360

Observation 7c8b3cf1-83f8-46c8-936f-37a1df93c09f · inbound

The Curious Case of Factuality Finetuning: Models' Internal Beliefs Can Improve Factuality cites this paper.

The Curious Case of Factuality Finetuning: Models' Internal Beliefs Can Improve Factuality A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 43

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no resolver link, observed 2026-08-06T18:26:31.820584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:26:31.820584Z digest=sha256:8b069798310a6bd33179099da6c6b7d4aaa9d74d96add6686cf82e01a3d9c967

Observation b0fa3d59-48b9-45e2-8276-fd43553d7299 · inbound

Enhancing Hallucination Detection via Future Context cites this paper.

Enhancing Hallucination Detection via Future Context A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 16

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verified exact
arxiv_id, observed 2026-05-19T03:22:00.880436Z

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=pdf_text observed=2026-05-19T03:20:00.756092Z digest=sha256:8b3e217557ce3fa6961da3326b98302edf95a1bf7e892b971ad2f23ba85ed92a

Observation 15ac6a5b-4793-4018-9382-52aee1ada4ae · inbound

MIRAGE-Bench: LLM Agent is Hallucinating and Where to Find Them cites this paper.

MIRAGE-Bench: LLM Agent is Hallucinating and Where to Find Them A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 29

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unresolved
no resolver link, observed 2026-08-06T13:06:38.977744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:06:38.977744Z digest=sha256:fc7774e765f564bf81b4b8d5bf9a571ecff41e666af2b752b7a76a6ef2020f6e

Observation 8eb7fdcf-3c82-44ad-9f36-56cb3c3aa7b0 · inbound

Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models cites this paper.

Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 37

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no resolver link, observed 2026-08-06T14:54:28.090926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:54:28.090926Z digest=sha256:2da2143a56ff32a7d938a60aa8239731757123185cfd2b33f5a4df70cc0e8517

Observation 26ba593d-1d6b-45c3-bde5-cbd3c8ec7b45 · inbound

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models cites this paper.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 12

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no resolver link, observed 2026-08-06T05:23:59.978259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:23:59.978259Z digest=sha256:9456d77b7ba62c4cdc336049b0b18120e6bf402d3e7adf60874dd7d489d50e80

Observation 503d8abf-1ff6-4d2e-adbd-31001499512a · inbound

Principled Detection of Hallucinations in Large Language Models via Multiple Testing cites this paper.

Principled Detection of Hallucinations in Large Language Models via Multiple Testing A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 22

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metadata mismatch
arxiv_id, observed 2026-05-18T20:46:51.581949Z

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=pdf_text observed=2026-05-18T20:44:52.898833Z digest=sha256:0c59fe9a6ab021b4cb56336d17ee4ccf0d8a8773c310dd93984b7f6bf56bd64a

Observation bdb081b2-a8b9-4f93-beff-4bb1f9ccb2f1 · inbound

Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality cites this paper.

Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 176

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no resolver link, observed 2026-08-05T15:38:55.102117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:38:55.102117Z digest=sha256:d77f7658bee4fd0a778e9361023e4282ba9ef3ec6af1d3eeaf7615c54aeea706

Observation 5dde900f-37ac-4974-952f-e7eefb06b8d7 · inbound

FActBench: A Benchmark for Fine-grained Automatic Evaluation of LLM-Generated Text in the Medical Domain cites this paper.

FActBench: A Benchmark for Fine-grained Automatic Evaluation of LLM-Generated Text in the Medical Domain A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 33

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no resolver link, observed 2026-08-05T11:49:37.219681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:49:37.219681Z digest=sha256:233b7a2a81bb789726eb605664eb4f32b588ba6f69988ade9ce4ca5a0eb335e0

Observation fbffc528-460e-49f1-a165-bee835351af4 · inbound

Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection cites this paper.

Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 29

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no resolver link, observed 2026-08-05T10:50:33.412508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:50:33.412508Z digest=sha256:679bc818d82f7e48212bfed5210f1b5efd9e1b4f99976a4d3c87c1e96d51bc3a

Observation 90612cb0-acac-4a68-aa36-b0018849d569 · inbound

Neural Message-Passing on Attention Graphs for Hallucination Detection cites this paper.

Neural Message-Passing on Attention Graphs for Hallucination Detection A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 50

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unresolved
no resolver link, observed 2026-08-04T13:52:12.628427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:52:12.628427Z digest=sha256:5c0a2030557124605344906b8f233a48bb5a74b40113848f27bc4c47f601d4d9

Observation dbadf06a-0d02-4769-9d21-68a0e55def89 · inbound

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs cites this paper.

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 76

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unresolved
no resolver link, observed 2026-08-03T12:42:37.546861Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:42:37.546861Z digest=sha256:a3308984d322c544c6d7eef3fa730c3fcfb70515c9e962cd1cae80e20218885e

Observation a1541f4b-8b50-490a-aea9-4e4a706b1ce4 · inbound

Geometry-Aware Hallucination Detection in Large Language Models cites this paper.

Geometry-Aware Hallucination Detection in Large Language Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 3

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malformed identifier
no resolver link, observed 2026-08-03T12:00:44.373700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:00:44.373700Z digest=sha256:11d3984d6f19f41b61c6583c4ec4238b95e08548f41213badc9682a591290071

Observation 0c56ae05-286a-476f-a8e9-d9f8cde308a5 · inbound

When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation cites this paper.

When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 41

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unresolved
no resolver link, observed 2026-08-03T00:03:24.512527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:03:24.512527Z digest=sha256:83e4fa15dc8e6781bbbb0000b93c7cce2d6cf4681082e0affc1999f192907a48

Observation 8f6a15ae-07e4-4c1a-acb0-6a4def1411cd · inbound

How do LLMs Compute Verbal Confidence cites this paper.

How do LLMs Compute Verbal Confidence A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 18

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metadata mismatch
arxiv_id, observed 2026-05-21T10:40:00.596553Z

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=pdf_text observed=2026-05-21T10:38:28.533485Z digest=sha256:0ece509f56a193c14c7e14e22c6f12bdd3e04b3004873347bb6ee4c91aab8f9d

Observation 75f22631-9d15-4400-91c9-705cfcd9820d · inbound

Steering the Verifiability of Multimodal AI Hallucinations cites this paper.

Steering the Verifiability of Multimodal AI Hallucinations A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 34

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verified exact
arxiv_id, observed 2026-05-11T00:45:50.415989Z

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=pdf_text observed=2026-05-10T18:19:45.405698Z digest=sha256:9e6e019cf818ebe8fc687d59e5bde28e5ef2a279f65fe597936d44c2a47eee84

Observation bf5b1655-afab-417b-88e9-f3c814500768 · inbound

DeepSeek Robustness Against Semantic-Character Dual-Space Mutated Prompt Injection cites this paper.

DeepSeek Robustness Against Semantic-Character Dual-Space Mutated Prompt Injection A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 32

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metadata mismatch
arxiv_id, observed 2026-05-11T09:41:00.398146Z

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=pdf_text observed=2026-05-10T15:54:24.013408Z digest=sha256:1a84c2ec31de5f487afce3c02dd152b9c5a9858f994808bec32e9534a0c94f73

Observation cbbd4851-4bc5-4a2d-b883-4470c0f57cb1 · inbound

Detection Without Correction: A Robust Asymmetry in Activation-Based Hallucination Probing cites this paper.

Detection Without Correction: A Robust Asymmetry in Activation-Based Hallucination Probing A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 20

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metadata mismatch
arxiv_id, observed 2026-05-15T09:15:21.031641Z

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=pdf_text observed=2026-05-15T09:11:33.508680Z digest=sha256:6de3afa298ddf946dbcc60de6743352e2cd5487269c2c8fd1e65d6a3061ba679

Observation 998207db-d550-4457-999a-9bf0908c13c4 · inbound

HalluScan: A Systematic Benchmark for Detecting and Mitigating Hallucinations in Instruction-Following LLMs cites this paper.

HalluScan: A Systematic Benchmark for Detecting and Mitigating Hallucinations in Instruction-Following LLMs A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:25:45.702491Z

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=2026-05-08T18:28:22.798874Z digest=sha256:3a1f9852bfd76772884440d846304f24d651851361e76f920ba3964f7d818e6e

Observation fb20e278-2e3d-4281-b1a5-998769a455e8 · inbound

HalluScan: A Systematic Benchmark for Detecting and Mitigating Hallucinations in Instruction-Following LLMs cites this paper.

HalluScan: A Systematic Benchmark for Detecting and Mitigating Hallucinations in Instruction-Following LLMs A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-25T06:50:27.955410Z

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=pdf_text observed=2026-05-25T06:49:16.755597Z digest=sha256:b7af3edd11ebdd17a62169062d373b5fde621e2a187d69cbc50e6082470e89ee

Observation 4a094346-2d62-407a-995a-d9c82c24ef86 · inbound

Agentic AIs Are the Missing Paradigm for Out-of-Distribution Generalization in Foundation Models cites this paper.

Agentic AIs Are the Missing Paradigm for Out-of-Distribution Generalization in Foundation Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:16:07.104867Z

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=pdf_text observed=2026-05-08T12:30:27.763123Z digest=sha256:eef894abfa23c83da018da372bb293e591290482baecb52973f50c0f4fc7bf2b

Observation e1423ca8-adb9-45d0-b37e-7d27623fd289 · inbound

Do No Harm? Hallucination and Actor-Level Abuse in Web-Deployed Medical Large Language Models cites this paper.

Do No Harm? Hallucination and Actor-Level Abuse in Web-Deployed Medical Large Language Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 65

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T05:53:59.424783Z

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=pdf_text observed=2026-05-21T05:49:55.738870Z digest=sha256:b1727f7645c9836aeb6c4fc84c207a80edee040667db82fc637edb6f8988e1c7

Observation ec010260-7b0d-4fcc-9e9e-7a1b32e3dc53 · inbound

MultiHaluDet: Multilingual Hallucination Detection via LLM Hidden State Probing cites this paper.

MultiHaluDet: Multilingual Hallucination Detection via LLM Hidden State Probing A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T12:34:38.674467Z

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=pdf_text observed=2026-06-30T12:29:59.165791Z digest=sha256:496788d0fb4dd06d75e5a902fdbb6272bb4cf24c8ed797e3c3c87c211ea52b4f

Observation 93b6662b-f75c-4b8d-a1db-a24c18bc1416 · inbound

Entropy Distribution as a Fingerprint for Hallucinations in Generative Models cites this paper.

Entropy Distribution as a Fingerprint for Hallucinations in Generative Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-06-29T12:13:26.660703Z

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=pdf_text observed=2026-06-29T12:10:43.626846Z digest=sha256:50598695ea72aab7659f5d117929f3281d0b114e6fd4ee586f9c28f90d89b2c1

Observation 4e0013bf-96a0-4e90-8ca1-9b710b9a6c9c · inbound

DrugClaw and DrugAudit: A Primary-Source-Grounded Agent and Authority-Aware Benchmark for Drug-Information Question Answering cites this paper.

DrugClaw and DrugAudit: A Primary-Source-Grounded Agent and Authority-Aware Benchmark for Drug-Information Question Answering A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 113

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:26:16.457116Z

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=2026-06-28T16:53:45.932631Z digest=sha256:75bab57194f26362a0a1c739f1f4c3e327181c952e934ac1725fa939e9a648b4

Observation 515fe6ff-9a46-488b-b9c0-be6b3c3b557a · inbound

Hybrid Adversarial Defence for Natural Language Understanding Tasks cites this paper.

Hybrid Adversarial Defence for Natural Language Understanding Tasks A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T07:26:46.315169Z

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=2026-06-28T06:55:02.191691Z digest=sha256:d4b91b803d38e82fbe4f26d5abc1d209e1bcd2c36e876d0734c37d5414ea6951

Observation 108acd16-8319-4554-b64f-411988fedf30 · inbound

AB-RAG: Adaptive Budgeted Retrieval-Augmented Generation for Reliable Question Answering cites this paper.

AB-RAG: Adaptive Budgeted Retrieval-Augmented Generation for Reliable Question Answering A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 32

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T09:24:32.919044Z

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=pdf_text observed=2026-06-30T09:12:12.732221Z digest=sha256:9a6cfb72f10b962a128993421f9cfa18e93321777af5a59f7b7129e0d217a187

Observation 108fd41d-c83b-47b2-99a0-9315a2a9306d · inbound

Reasoning Denoiser: Denoising Reasoning Traces for Hallucination Detection in Large Reasoning Models cites this paper.

Reasoning Denoiser: Denoising Reasoning Traces for Hallucination Detection in Large Reasoning Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-01T05:52:43.452222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:52:43.452222Z digest=sha256:b5c005862a23e7f97b86cb28089e34507034209ddce3857440e5e23bb8a241bb

Observation f1f4a2c9-2987-45b3-ab40-b057bedd3de6 · inbound

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models cites this paper.

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 64

Resolution
unresolved
no resolver link, observed 2026-07-31T23:32:10.117439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:32:10.117439Z digest=sha256:7319a7f4f5b39f423f68bab5dd9b354408b3526ec1fd48dd47d5437e39f8993f

Observation 22a26c0b-3a94-46f1-b3bf-48695681c16f · inbound

Before Agents Speak: Pre-hoc Failure Risk Inference in Multi-Agent Systems cites this paper.

Before Agents Speak: Pre-hoc Failure Risk Inference in Multi-Agent Systems A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 92

Resolution
unresolved
no resolver link, observed 2026-07-30T19:40:15.143054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T19:40:15.143054Z digest=sha256:d1855b83156dd4d7de2df8ffceb6ca3c634c29e2b06699425a279f81c8871d0e