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Paper Citation Record · LEDGER

Are Large Language Models Good Fact Checkers: A Preliminary Study

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.17355.

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

pith.paper-citation-record.v1
2311.17355 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:24:39.838917Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:50:56.927168Z

Reference resolution

0 of 0 outbound references displayed

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

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 ede38a1f-56fd-4670-b35d-8becc88f6c36 · inbound

When Scale Meets Diversity: Evaluating Language Models on Fine-Grained Multilingual Claim Verification cites this paper.

When Scale Meets Diversity: Evaluating Language Models on Fine-Grained Multilingual Claim Verification Are Large Language Models Good Fact Checkers: A Preliminary Study

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T13:24:39.838917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T13:24:39.838917Z digest=sha256:c9e34a17182ba067e4ba32563122325f2c12aacc7491bcf93b13fbcac9bb6015

Observation 0d5eb7ef-9d76-477d-9c69-f85f44687f67 · inbound

Can LLMs Take Retrieved Information with a Grain of Salt? cites this paper.

Can LLMs Take Retrieved Information with a Grain of Salt? Are Large Language Models Good Fact Checkers: A Preliminary Study

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:50:56.930130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-11T01:02:34.197356Z digest=sha256:9115b4de08df9fbac4d303b589b1e2ec89ed77180b61107305d7894b98443ef8