Paper Citation Record · LEDGER

Confidence in the Reasoning of Large Language Models

As of 14 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 2 inbound Pith citation observations for arXiv:2412.15296.

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

pith.paper-citation-record.v1
2412.15296 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:03:42.611576Z

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:14:52.063511Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T05:37:36.077846Z

Reference resolution

2 of 2 outbound references displayed

verified exact0
verified fuzzy1
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5a21bb38-2a62-404c-a4fe-d571dbcff3da · outbound

This paper cites to generate executable plans autonomously is rather limited, with the best model (GPT4) having an average success rate of ∼ 12% across the domains.

Confidence in the Reasoning of Large Language Models to generate executable plans autonomously is rather limited, with the best model (GPT4) having an average success rate of ∼ 12% across the domains

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:03:42.767160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8e67007f-e5f8-4ec5-8aee-9224a275ce83 · outbound

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

Confidence in the Reasoning of Large Language Models Language Models (Mostly) Know What They Know

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T12:03:42.611576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 20eaaa64-2e50-469b-beeb-6403e792bc24 · inbound

Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident, Especially When They are Wrong cites this paper.

Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident, Especially When They are Wrong Confidence in the Reasoning of Large Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:37:36.081259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 925c3100-9e08-4ad1-b657-35d777dc3909 · inbound

From Divergence to Consensus: Evaluating the Role of Large Language Models in Facilitating Agreement through Adaptive Strategies cites this paper.

From Divergence to Consensus: Evaluating the Role of Large Language Models in Facilitating Agreement through Adaptive Strategies Confidence in the Reasoning of Large Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T16:14:52.063511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.