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Paper Citation Record · LEDGER

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2508.01862.

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

pith.paper-citation-record.v1
2508.01862 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:23:59.978259Z

measured 13 of 13 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:42:27.753911Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation df04d0d2-5a03-4c6e-825a-c4f556f516bc · outbound

This paper cites and Mitchell, T.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models and Mitchell, T

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:01.695465Z

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=2026-08-06T05:23:58.803204Z digest=sha256:f53f311dc7decdaf95e5001bedf0609677d6ecd98d8214d943d3b2637fdf1d3b

Observation 1a092e7e-955f-4292-88af-322abf81fa8e · outbound

This paper cites an unresolved cited work.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:24:01.431065Z

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=2026-08-06T05:23:59.002705Z digest=sha256:1def5eff20d7a9b7995a41a2f13091a448850011c7e8ca1c9f51391b1b5d0d55

Observation 6c7e85fb-98af-48f8-86e1-680ea58573af · outbound

This paper cites Language Models (Mostly) Know What They Know.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models Language Models (Mostly) Know What They Know

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T05:23:59.163411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:23:59.163411Z digest=sha256:eaf2630fa5b2e673c6b04eb535fa1936a0b69efbf382197525bacdbc4f2fc240

Observation 38d56c73-34c6-40fd-b74c-5e1c9b80c8de · outbound

This paper cites On faithfulness and factuality in abstractive summarization.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models On faithfulness and factuality in abstractive summarization

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:00.975628Z

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=2026-08-06T05:23:59.440913Z digest=sha256:bcd891abab9c28bffee1ee38cf319368415f6696be14c9a2fd35f2581d207368

Observation 3922976b-1d14-47c8-be79-2dcc186fe842 · outbound

This paper cites Kilt: a benchmark for knowledge intensive language tasks.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models Kilt: a benchmark for knowledge intensive language tasks

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:00.732844Z

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=2026-08-06T05:23:59.573740Z digest=sha256:8511395e60537a2b317a613f654b61d29b6f42aebe6ddd8041712e63036974f8

Observation e58f5340-af50-4673-a84a-48a9de34dc65 · outbound

This paper cites The curious case of hallucinations in neural machine transla- tion.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models The curious case of hallucinations in neural machine transla- tion

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:00.587292Z

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=2026-08-06T05:23:59.657935Z digest=sha256:0e21dc894a0abd783c94f425bd817605a4038f7ff80bdf32ed9ba244ddb0bd7d

Observation 2e4a1358-823d-4b3c-a8d3-b2a2da09ad85 · outbound

This paper cites Fever: a large-scale dataset for fact extraction and verification.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models Fever: a large-scale dataset for fact extraction and verification

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:00.377050Z

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=2026-08-06T05:23:59.793721Z digest=sha256:e20a121a6d194a2e65b8c155d1ebec35f423850287282928d2d3ef35b740d959

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

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

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

Resolution
unresolved
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=sha256:5964cddc35fa8a7b56d1ceecc58d44cea4fef9f4ff63d183f8f735b1b5c478e4

Observation 0e257a96-023e-4eee-8c10-a9eead34d43a · outbound

This paper cites Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-06T05:23:59.897211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:23:59.897211Z digest=sha256:cc4fdd8bea748010366b8cfb1a4251da8c33b2120f2b7b11dcd05497a7b9ba7b

Observation 3880a93d-eaa2-4307-ad31-bdc26af81113 · outbound

This paper cites an unresolved cited work.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models Unresolved cited work

Reference 2021

Resolution
unresolved
raw_fallback, observed 2026-08-06T05:24:01.170425Z

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=2026-08-06T05:23:59.263461Z digest=sha256:37b7b5bd8389a318d75be0b05d4d09ce8614a6885f65ac68a2334babb6b008d4

Observation 2d52b81a-4333-4c9f-966e-f7504f35c85f · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T05:23:59.077640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:23:59.077640Z digest=sha256:ab950d4225690cf62e401bf2d46b81c79de404266ebcf06ee2e3e31c7f2d4daf

Observation a5842b6e-284a-4084-b50b-91ecb1d5a297 · outbound

This paper cites LM vs LM: Detecting Factual Errors via Cross Examination.

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models LM vs LM: Detecting Factual Errors via Cross Examination

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T05:23:58.876380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:23:58.876380Z digest=sha256:81ddbf4eee5f57c2d8300ba95047ec56e3fcdfed7a31281b77c38502502160af

Pith citing papers

Observation d55f69c9-5251-47f3-bd5c-058b17863403 · inbound

Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation cites this paper.

Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-03T15:42:27.753911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:42:27.753911Z digest=sha256:de8b8188255714b7ce344d3fc3d70f89787e105318c35bb8ef25cadc8476f43c