Paper Citation Record · LEDGER

Progressive-Hint Prompting Improves Reasoning in Large Language Models

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2304.09797.

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

pith.paper-citation-record.v1
2304.09797 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:04:52.743835Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

33
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6479af65-cbc8-473f-98ba-bfff0b518659 · inbound

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate cites this paper.

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-05-14T00:00:15.782774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bc18135b-e267-4327-9f11-9716cc534f04 · inbound

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning cites this paper.

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-17T23:46:39.635998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation aa88305c-8476-475a-9e5e-d2536fe638b4 · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T08:12:35.363571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fbd24e7c-57ef-4308-94ba-c3d502e5e67a · inbound

A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration cites this paper.

A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:05:25.950816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 303d8715-e29f-4264-a3a7-da36c11dd216 · inbound

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 109

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:42:10.665249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 591c6019-1042-4d76-a86f-621fffd4d86f · inbound

DRF: LLM-AGENT Dynamic Reputation Filtering Framework cites this paper.

DRF: LLM-AGENT Dynamic Reputation Filtering Framework Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T05:04:52.743835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef08b98-6e59-488f-8d80-91a7c10644ca · inbound

Asking LLMs to Verify First is Almost Free Lunch cites this paper.

Asking LLMs to Verify First is Almost Free Lunch Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T21:03:19.486849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29ad87a1-9d94-4b98-9283-e7e9e54637f2 · inbound

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions cites this paper.

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 118

Resolution: unresolved; no resolver link, observed 2026-08-02T23:04:39.712305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 246359fe-09db-424f-b543-2fcf236e6911 · inbound

SeLaR: Selective Latent Reasoning in Large Language Models cites this paper.

SeLaR: Selective Latent Reasoning in Large Language Models Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:35:49.606877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9f2f5cb0-c1c5-4097-becb-af445dd2dc3f · inbound

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models cites this paper.

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 129

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:05:09.148944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 90dc0011-2bfa-4b94-aa4a-9a55b1764350 · inbound

Conflict-Resilient Multi-Agent Reasoning via Signed Graph Modeling cites this paper.

Conflict-Resilient Multi-Agent Reasoning via Signed Graph Modeling Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:48:04.386100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 766be3ab-74ac-4abb-b0f0-714dc1f0e2be · inbound

An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods cites this paper.

An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T15:24:49.555966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 27e42f6f-ac53-40db-bac1-71683ba8fe1b · inbound

StepFinder: A Temporal Semantic Framework for Failure Attribution in Multi-Agent Systems cites this paper.

StepFinder: A Temporal Semantic Framework for Failure Attribution in Multi-Agent Systems Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:16:34.025865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1a8b30ef-032d-4beb-99f5-a9cdfb02e038 · inbound

Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization cites this paper.

Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-08T22:25:39.491495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 92ca9c9d-b4e6-48ea-8da8-f6c54236be20 · inbound

Sample More, Reflect Less: Self-Refine and Reflexion Lose to Repeated Sampling at Equal Token Cost, from 1.5B to 7B cites this paper.

Sample More, Reflect Less: Self-Refine and Reflexion Lose to Repeated Sampling at Equal Token Cost, from 1.5B to 7B Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-31T03:19:01.329887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.