Paper Citation Record · LEDGER

Gauging Overprecision in LLMs: An Empirical Study

As of 17 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2504.12098.

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

pith.paper-citation-record.v1
2504.12098 v2

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:25.730770Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

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 exact1
verified fuzzy6
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dfb07a1d-3d2a-4e3a-857d-eb88292dcc40 · outbound

This paper cites GPT-4 Technical Report.

Gauging Overprecision in LLMs: An Empirical Study GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:25.678940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5436ffcf-941d-493e-8d4d-9f1e2dc071d6 · outbound

This paper cites and Valdenegro-Toro, M.

Gauging Overprecision in LLMs: An Empirical Study and Valdenegro-Toro, M

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:25.867624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 36c80c1c-0bb1-447f-8e0f-5eeeb16b62ad · outbound

This paper cites ’instruction’ represents the abbreviation used in the paper for a particular set of instructions.

Gauging Overprecision in LLMs: An Empirical Study ’instruction’ represents the abbreviation used in the paper for a particular set of instructions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:25.816055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5ee22de5-6ef7-42fc-8414-b82456907807 · outbound

This paper cites L., and Howe, B.

Gauging Overprecision in LLMs: An Empirical Study L., and Howe, B

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:25.829792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ed370e29-3644-44ca-a72f-5afda0ed646f · outbound

This paper cites AsthmaBot: Multi-modal, Multi-Lingual Retrieval Augmented Generation For Asthma Patient Support.

Gauging Overprecision in LLMs: An Empirical Study AsthmaBot: Multi-modal, Multi-Lingual Retrieval Augmented Generation For Asthma Patient Support

Reference 1982

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:40:25.793362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 037777c8-2283-4be3-9b63-f12d1e1b9447 · outbound

This paper cites Measuring massive multitask language understanding.

Gauging Overprecision in LLMs: An Empirical Study Measuring massive multitask language understanding

Reference 1997

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:25.854691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7ea8e308-62e1-4ecd-9568-b7149b0517dd · outbound

This paper cites SelfCheckGPT: Zero-resource black-box hallucination detection for gen- erative large language models.

Gauging Overprecision in LLMs: An Empirical Study SelfCheckGPT: Zero-resource black-box hallucination detection for gen- erative large language models

Reference 1999

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:25.842012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dd49d59b-a810-483d-a2d4-dab27e8b7541 · outbound

This paper cites Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments.

Gauging Overprecision in LLMs: An Empirical Study Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:25.721749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a0343b5-5791-4366-8cc2-d2b6d502dfdc · outbound

This paper cites R., et al.

Gauging Overprecision in LLMs: An Empirical Study R., et al

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:25.689145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0262d08d-871e-45a2-8381-9b6274f6335e · outbound

This paper cites Shifting attention to relevance: Towards the uncertainty estimation of large language models.

Gauging Overprecision in LLMs: An Empirical Study Shifting attention to relevance: Towards the uncertainty estimation of large language models

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:25.881834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1853fa88-ca7b-4022-b85e-beb59c90190f · outbound

This paper cites doi: 10.18653/v1/2023.

Gauging Overprecision in LLMs: An Empirical Study doi: 10.18653/v1/2023

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:25.712549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c367651-ab9f-48d5-9922-f5de3ec84be6 · outbound

This paper cites Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation.

Gauging Overprecision in LLMs: An Empirical Study Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:25.717084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.