Paper Citation Record · LEDGER

Incoherent Probability Judgments in Large Language Models

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.16646.

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

pith.paper-citation-record.v1
2401.16646 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 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:57:38.195091Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:58:57.602855Z

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 323d11a2-1279-4e3d-ba0d-411be7d6f82c · inbound

Let's Think Var-by-Var: Large Language Models Enable Ad Hoc Probabilistic Reasoning cites this paper.

Let's Think Var-by-Var: Large Language Models Enable Ad Hoc Probabilistic Reasoning Incoherent Probability Judgments in Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T23:54:15.634583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f46f4d46-b1b5-4524-b971-d68d47f41c96 · inbound

Steering Risk Preferences in Large Language Models by Aligning Behavioral and Neural Representations cites this paper.

Steering Risk Preferences in Large Language Models by Aligning Behavioral and Neural Representations Incoherent Probability Judgments in Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T20:57:38.195091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd18fa2d-5a8c-4ce0-b329-e413ad30db57 · inbound

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems cites this paper.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Incoherent Probability Judgments in Large Language Models

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:39.192857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c9b5ad9-9bb1-41fe-8caf-1ae316248f9b · inbound

Designing Psychometric Bias Measures for ChatBots: An Application to Racial Bias Measurement cites this paper.

Designing Psychometric Bias Measures for ChatBots: An Application to Racial Bias Measurement Incoherent Probability Judgments in Large Language Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:12:51.790214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2aedb408-67b7-470c-bdaa-3a3221e7b7c2 · inbound

Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games cites this paper.

Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games Incoherent Probability Judgments in Large Language Models

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:58:57.604469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b7e2571f-5c50-4070-80ac-62200738cc4d · inbound

Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models cites this paper.

Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models Incoherent Probability Judgments in Large Language Models

Reference 156

Resolution: unresolved; no resolver link, observed 2026-08-01T23:43:21.328678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.