Paper Citation Record · LEDGER

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning

As of 23 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2602.02979.

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

pith.paper-citation-record.v1
2602.02979 v3

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:14:22.701235Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

49 of 49 outbound references displayed

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unresolved49
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Outbound references

Observation 87d0fa1f-0626-4e36-a24f-8cb1dae340ff · outbound

This paper cites write newline.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning write newline

Reference 1

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Observation 1a45c0f4-7875-4ed4-8853-ee4539f65de5 · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning gpt-oss-120b & gpt-oss-20b Model Card

Reference 2

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Observation bdfcc90d-8e92-4083-a330-075d0d36cdc7 · outbound

This paper cites The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:17.279744Z

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Observation 69de20ef-bf47-4540-aaa3-41cb06dc5a84 · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:17.390378Z

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Observation e32f2d2d-3250-43b9-bbf7-511323954271 · outbound

This paper cites Self-Questioning Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Self-Questioning Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:17.543228Z

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Observation 25610b30-6f73-42cf-be21-e10395ced2c0 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Evaluating Large Language Models Trained on Code

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:17.644273Z

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Observation e4e45190-6ff2-466b-961e-4204a8676826 · outbound

This paper cites Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:17.752684Z

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Observation 737037a8-e47b-44d4-a264-54666cf8bb22 · outbound

This paper cites F., Leike, J., Brown, T., Martic, M., Legg, S., and Amodei, D.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning F., Leike, J., Brown, T., Martic, M., Legg, S., and Amodei, D

Reference 8

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Observation d617b099-8cf9-4b7b-9dc2-bb66070de29e · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:17.899029Z

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Observation 3d6a929b-8e45-4dd7-83e8-5f52b1200b4f · outbound

This paper cites Process Reinforcement through Implicit Rewards.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Process Reinforcement through Implicit Rewards

Reference 10

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Observation 09b938cb-cfa9-409d-9fde-7fd96d8601ba · outbound

This paper cites Reinforcement Pre-Training.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Reinforcement Pre-Training

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:18.061552Z

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Observation 6d6214f2-eaf5-46ca-b93c-e6fec8f28563 · outbound

This paper cites The Llama 3 Herd of Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning The Llama 3 Herd of Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:18.148904Z

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Observation f86ca8b5-11b4-4ac4-b1b0-76bbca2e5fc4 · outbound

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

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 13

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Observation 1d40c09b-d99b-468c-9ba5-51506692e497 · outbound

This paper cites O lympiad B ench: A challenging benchmark for promoting AGI with olympiad-level bilingual multimodal scientific problems.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning O lympiad B ench: A challenging benchmark for promoting AGI with olympiad-level bilingual multimodal scientific problems

Reference 14

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Observation 8daffe21-dfc4-4bd5-878a-b4ee0fd211ea · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Measuring Mathematical Problem Solving With the MATH Dataset

Reference 15

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Observation 7a846845-f5a8-43b3-b42f-54e359f75bee · outbound

This paper cites Cooper: Co-Optimizing Policy and Reward Models in Reinforcement Learning for Large Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Cooper: Co-Optimizing Policy and Reward Models in Reinforcement Learning for Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:18.632040Z

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Observation 5fb056ad-3db9-455a-9ba4-619a857ff0e8 · outbound

This paper cites R-Zero: Self-Evolving Reasoning LLM from Zero Data.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning R-Zero: Self-Evolving Reasoning LLM from Zero Data

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:18.752065Z

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Observation fb33b96c-a663-42ee-8cf6-7604f252f535 · outbound

This paper cites OpenAI o1 System Card.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning OpenAI o1 System Card

Reference 18

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Observation bc67d132-ce79-4bb1-b1b7-d2e82aa7e73c · outbound

This paper cites PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:18.928775Z

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Observation 04c1710f-cb6e-4b6a-8800-1b409e358e42 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.051690Z

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Observation c7a19091-6e30-466f-9050-cb40ebc128d1 · outbound

This paper cites Solving Quantitative Reasoning Problems with Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Solving Quantitative Reasoning Problems with Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.142903Z

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Observation 80755571-d9f4-4a77-9222-4be56575688e · outbound

This paper cites Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.263434Z

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Observation 27b9735b-8a94-4cb8-bfd3-6a74ed075534 · outbound

This paper cites URPO: A Unified Reward & Policy Optimization Framework for Large Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning URPO: A Unified Reward & Policy Optimization Framework for Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.399777Z

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Observation f5c69e64-3f56-4297-8e6e-5f40264c8371 · outbound

This paper cites AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.549625Z

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Observation fc97f02f-9939-460d-b733-43ff7bb1570b · outbound

This paper cites Gpt-5 system card.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Gpt-5 system card

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.689456Z

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Observation 4a99a263-3129-4a56-b36a-407951cbbd24 · outbound

This paper cites Openai o3 and o4-mini system card.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Openai o3 and o4-mini system card

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.817165Z

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Observation 12838577-31e1-47f6-b1f9-5296e72813f5 · outbound

This paper cites Training language models to follow instructions with human feedback.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Training language models to follow instructions with human feedback

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.947935Z

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Observation 3601a53e-9544-4920-b9c7-75b34b5a2b09 · outbound

This paper cites Maximizing Confidence Alone Improves Reasoning.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Maximizing Confidence Alone Improves Reasoning

Reference 28

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Observation 60aafde8-049e-4852-82cd-062df4e42f3c · outbound

This paper cites ChatDev: Communicative Agents for Software Development.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning ChatDev: Communicative Agents for Software Development

Reference 29

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Observation b81d792d-609f-42ee-99b0-75671d10419e · outbound

This paper cites Proximal Policy Optimization Algorithms.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 30

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Observation b8acca25-d9e8-4c0c-82c8-b61e1cb98086 · outbound

This paper cites an unresolved cited work.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Unresolved cited work

Reference 31

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Observation 0fabeef2-9cce-4689-85ea-d4369ba374ef · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 32

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Observation 0d8a5bc1-fea8-416d-9c88-6fb3901f2fa3 · outbound

This paper cites Hybridflow: A flexible and efficient rlhf framework.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Hybridflow: A flexible and efficient rlhf framework

Reference 33

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Observation 32557d67-3451-44be-8156-77395016f9c0 · outbound

This paper cites Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 34

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Observation 7f367450-1201-4965-a556-2b4be6eab8a3 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Kimi K2: Open Agentic Intelligence

Reference 35

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Observation 3383bd60-e72a-4dbf-ac1b-00724e58fe4d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning LLaMA: Open and Efficient Foundation Language Models

Reference 36

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Observation b4f89082-9116-4c21-a8dc-0b28d253485b · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Zephyr: Direct Distillation of LM Alignment

Reference 37

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Observation 135e414e-7f4a-4229-876c-70cf501e6e31 · outbound

This paper cites V., Chi, E.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning V., Chi, E

Reference 38

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Observation 5877dcad-ab33-452d-90da-745304b5d0a3 · outbound

This paper cites OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling

Reference 39

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Observation a0df4921-1f7b-4bd2-be47-c0941eb40e2a · outbound

This paper cites V., Zhou, D., et al.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning V., Zhou, D., et al

Reference 40

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Observation b896a909-8106-4d06-ac64-1436ef0624b9 · outbound

This paper cites Self-rewarding correction for mathematical reasoning.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Self-rewarding correction for mathematical reasoning

Reference 41

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Observation cdf5c098-156d-4097-a352-632d13f6c65b · outbound

This paper cites Qwen2 Technical Report.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Qwen2 Technical Report

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:21.778638Z

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Observation 23a6939e-eb50-4155-bcc8-347fa703c964 · outbound

This paper cites Self-Rewarding Language Models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Self-Rewarding Language Models

Reference 44

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Observation dfd36174-b9ca-47bb-a361-d09a6b57de2d · outbound

This paper cites S., and Katabi, D.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning S., and Katabi, D

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:21.969612Z

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Observation c101a8eb-45cf-44a7-a4e0-633897d475cb · outbound

This paper cites Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:22.069080Z

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Observation 9fcaacfb-fa23-4a17-aee4-351c5a09750b · outbound

This paper cites Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback

Reference 47

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Observation 09c111ba-ea9e-4141-9985-0fb9fa94f850 · outbound

This paper cites Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Absolute Zero: Reinforced Self-play Reasoning with Zero Data

Reference 48

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Observation dc6b080e-c3c7-4fd8-8e92-ba8f2fb6dec4 · outbound

This paper cites TTRL: Test-Time Reinforcement Learning.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning TTRL: Test-Time Reinforcement Learning

Reference 49

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Observation e33cb627-a715-4a13-bd31-0c3f31276d91 · outbound

This paper cites Self-adapting language models.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Self-adapting language models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:22.701235Z

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Pith citing papers

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