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Paper Citation Record · LEDGER

Meta-R1: Empowering Large Reasoning Models with Metacognition

As of 20 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 2 inbound Pith citation observations for arXiv:2508.17291.

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

pith.paper-citation-record.v1
2508.17291 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:11:34.272694Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:50:30.527738Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T15:50:31.812770Z

Reference resolution

7 of 7 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation deb5ec6d-e40b-44fd-bca3-6edf94a68dc6 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Meta-R1: Empowering Large Reasoning Models with Metacognition Training Verifiers to Solve Math Word Problems

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T17:11:34.239740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:11:34.239740Z digest=sha256:60905a072c863a2ae3bcb7f6dd320c542705c8a5d1fcb131445f8530a6545391

Observation 91f39ef6-4299-47c6-9090-e41eab76ff74 · outbound

This paper cites Aime problems and solutions.

Meta-R1: Empowering Large Reasoning Models with Metacognition Aime problems and solutions

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:11:34.408130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T17:11:34.246817Z digest=sha256:50a1de3121e422aba31e5a6b36a6ad9857cb374b08bfd380e4476cbeb91b4dec

Observation 2e97f1d5-8665-48dd-a883-e1934442f8e6 · outbound

This paper cites Measuring mathematical problem solving with the MATH dataset.

Meta-R1: Empowering Large Reasoning Models with Metacognition Measuring mathematical problem solving with the MATH dataset

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T17:11:34.251803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:11:34.251803Z digest=sha256:bd8b7257646f16de13db92732e47cb91a104c0d86a7b3d9395848d30f3005ff4

Observation a98f811a-728f-491f-8693-b1bf5943c0a7 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Meta-R1: Empowering Large Reasoning Models with Metacognition DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T17:11:34.256583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:11:34.256583Z digest=sha256:deed8e47218febe78232940b01b34867550596193425073e4a2d77f4a9afaff5

Observation fa915664-f2aa-48d5-9810-636788226194 · outbound

This paper cites Qwen2.5 technical report, 2025.

Meta-R1: Empowering Large Reasoning Models with Metacognition Qwen2.5 technical report, 2025

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T17:11:34.262351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:11:34.262351Z digest=sha256:9c5bb44666596139789622d0806243a2f5e5d912c3f3ba71442a5332b59214ad

Observation 20ddb198-bf85-48dd-a7ab-c8529f0a1bf8 · outbound

This paper cites Qwen2.5: A party of foundation models, September 2024.

Meta-R1: Empowering Large Reasoning Models with Metacognition Qwen2.5: A party of foundation models, September 2024

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T17:11:34.267515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:11:34.267515Z digest=sha256:a2f83e28edb3732823521bf3d424288d3cd0f6192e7adde593ca5f2377b89c79

Observation 4dfc521c-fb68-4bfb-939a-6cadb5330996 · outbound

This paper cites Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency.

Meta-R1: Empowering Large Reasoning Models with Metacognition Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T17:11:34.272694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:11:34.272694Z digest=sha256:38e610843c23e87234a8fa9f6e285f6ae8aa869762e0b8c649049c24e3d40dbb

Pith citing papers

Observation a8aa4e49-60f9-4cfd-8f75-9e34b490732c · inbound

Verifying Meta-Awareness via Predictive Rewards in Reasoning Models cites this paper.

Verifying Meta-Awareness via Predictive Rewards in Reasoning Models Meta-R1: Empowering Large Reasoning Models with Metacognition

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-15T15:50:31.819104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T15:50:30.527738Z digest=sha256:27fa2f3b73ec9c5111d7fad8330748c92e65d003391394afb5c5dd6a6e348e7f

Observation 719f3b58-d6f2-4d56-a91b-5612c7bdfb56 · inbound

PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs cites this paper.

PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs Meta-R1: Empowering Large Reasoning Models with Metacognition

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-02T13:27:19.712607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T13:27:19.712607Z digest=sha256:d0a43aacdfb0f8193215b9f6a2a08b289327394658709c77c87cc28ffd16df4c