Paper Citation Record · LEDGER

Generating Benchmarks for Factuality Evaluation of Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2307.06908.

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

pith.paper-citation-record.v1
2307.06908 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:37:07.929837Z

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

8
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 56ed0ae3-23c2-4535-8c2e-3b84c1e8ec7e · inbound

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models cites this paper.

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models Generating Benchmarks for Factuality Evaluation of Language Models

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-16T13:21:24.351633Z

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.

Observation f5b3295e-cdaa-493a-a14e-bdf124f60f91 · inbound

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

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions Generating Benchmarks for Factuality Evaluation of Language Models

Reference 234

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:46:27.823764Z

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.

Observation 6316a058-a3bd-4174-b5a2-1b8130bee357 · inbound

Corrective Retrieval Augmented Generation cites this paper.

Corrective Retrieval Augmented Generation Generating Benchmarks for Factuality Evaluation of Language Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-12T11:19:17.184643Z

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.

Observation 3df65717-16a5-4af0-bc62-4eba90a4ca4f · inbound

Improve Decoding Factuality by Token-wise Cross Layer Entropy of Large Language Models cites this paper.

Improve Decoding Factuality by Token-wise Cross Layer Entropy of Large Language Models Generating Benchmarks for Factuality Evaluation of Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T05:37:07.929837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e0ee678-bad3-4e4b-b341-d9225175a12d · inbound

Fact or Facsimile? Evaluating the Factual Robustness of Modern Retrievers cites this paper.

Fact or Facsimile? Evaluating the Factual Robustness of Modern Retrievers Generating Benchmarks for Factuality Evaluation of Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T15:09:22.308089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0fb7559-251e-4e31-96a7-e2b72764e4ab · inbound

Mitigating Hallucinations in Large Language Models Via Decoder Layer Skipping cites this paper.

Mitigating Hallucinations in Large Language Models Via Decoder Layer Skipping Generating Benchmarks for Factuality Evaluation of Language Models

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T18:32:29.025942Z

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.