Paper Citation Record · LEDGER

Metacognitive Prompting Improves Understanding in Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2308.05342.

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

pith.paper-citation-record.v1
2308.05342 v4

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 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:18:06.542367Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:39:41.832595Z

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 038b0e5a-9e7a-4927-b072-1ceb8dd715fc · inbound

Do Large Vision-Language Models Distinguish between the Actual and Apparent Features of Illusions? cites this paper.

Do Large Vision-Language Models Distinguish between the Actual and Apparent Features of Illusions? Metacognitive Prompting Improves Understanding in Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:18:06.542367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 826d8912-74f2-4584-b80b-3f1c67ba4610 · inbound

Bhatt Conjectures: On Necessary-But-Not-Sufficient Benchmark Tautology for Human Like Reasoning cites this paper.

Bhatt Conjectures: On Necessary-But-Not-Sufficient Benchmark Tautology for Human Like Reasoning Metacognitive Prompting Improves Understanding in Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:15:30.612252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 449b75a8-8dd2-4d9c-b75c-5fc000c7d5c1 · inbound

Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap cites this paper.

Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap Metacognitive Prompting Improves Understanding in Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T18:40:06.015943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0faa58fa-497b-461b-a3d2-0cc3c530e260 · inbound

Referential ambiguity and clarification requests: comparing human and LLM behaviour cites this paper.

Referential ambiguity and clarification requests: comparing human and LLM behaviour Metacognitive Prompting Improves Understanding in Large Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T17:35:20.431046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 458711aa-ebd6-402c-8104-1ace64a19175 · inbound

AccessGuru: Leveraging LLMs to Detect and Correct Web Accessibility Violations in HTML Code cites this paper.

AccessGuru: Leveraging LLMs to Detect and Correct Web Accessibility Violations in HTML Code Metacognitive Prompting Improves Understanding in Large Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T14:36:19.915910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc8f8d58-00db-45eb-8704-fe15b24a7dfa · inbound

Latent Confidence Alignment for LLM Self-Assessment cites this paper.

Latent Confidence Alignment for LLM Self-Assessment Metacognitive Prompting Improves Understanding in Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:39:41.834113Z

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.