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Paper Citation Record · LEDGER

Why Can Large Language Models Generate Correct Chain-of-Thoughts?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.13571.

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

pith.paper-citation-record.v1
2310.13571 v4

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 2026-08-07T05:14:47.475664Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:13:58.686327Z

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 8bd2bb36-4635-4235-80c5-9c500646881b · inbound

A Survey on Large Language Models for Mathematical Reasoning cites this paper.

A Survey on Large Language Models for Mathematical Reasoning Why Can Large Language Models Generate Correct Chain-of-Thoughts?

Reference 1950

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:47.475664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:47.475664Z digest=sha256:719d10836a457756df7dc91389c2fb37fa35bdec0d42973496b3bf5a22d2acfc

Observation 1346cce3-87e7-4674-beb9-006c6e534a55 · inbound

On the Cost and Benefit of Chain of Thought: A Learning-Theoretic Perspective cites this paper.

On the Cost and Benefit of Chain of Thought: A Learning-Theoretic Perspective Why Can Large Language Models Generate Correct Chain-of-Thoughts?

Reference 90

Resolution
malformed identifier
arxiv_id, observed 2026-05-21T05:13:58.688077Z

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=pdf_text observed=2026-05-21T05:09:37.588841Z digest=sha256:54afc822e56734f9980612be7d191298b2802f8769864b523301edb3d1879157