Paper Citation Record · LEDGER

Improving RL Exploration for LLM Reasoning through Retrospective Replay

As of 19 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 6 inbound Pith citation observations for arXiv:2504.14363.

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

pith.paper-citation-record.v1
2504.14363 v2

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:53:29.001062Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:30:38.055667Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:59:40.189087Z

Reference resolution

56 of 56 outbound references displayed

verified exact1
verified fuzzy9
unresolved45
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 888524d1-e700-4d13-b272-6e7915a7e389 · outbound

This paper cites IEEE Signal Processing Magazine 34(6), 26–38 (2017).

Improving RL Exploration for LLM Reasoning through Retrospective Replay IEEE Signal Processing Magazine 34(6), 26–38 (2017)

Reference 1

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Observation dae19bd0-8887-42d9-9b17-6e1071ebc1e6 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:27.575439Z

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Unavailable: canonical work link unavailable.

Observation c90a7971-3e79-4e58-bc1b-850676693ab8 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:27.666657Z

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Observation 9c39bf08-9c78-4d61-9ebe-bcffa6d48bb5 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Improving RL Exploration for LLM Reasoning through Retrospective Replay DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 4

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Observation d20b8933-9a52-46b1-bfc6-e781c9329f0a · outbound

This paper cites DocFusion: A Unified Framework for Document Parsing Tasks.

Improving RL Exploration for LLM Reasoning through Retrospective Replay DocFusion: A Unified Framework for Document Parsing Tasks

Reference 5

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Observation 42bc350b-17e5-423b-92a7-b384c0860eac · outbound

This paper cites PanGu-Coder: Program Synthesis with Function-Level Language Modeling.

Improving RL Exploration for LLM Reasoning through Retrospective Replay PanGu-Coder: Program Synthesis with Function-Level Language Modeling

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:27.679663Z

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Observation ad4659b5-0974-46d4-a975-452382807278 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Training Verifiers to Solve Math Word Problems

Reference 7

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Observation 65229ffc-8d53-46e3-b205-549ceff1b21c · outbound

This paper cites In: 2008 Interna- tional Conference on Computational Intelligence for Modelling Control Automa- tion.

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: 2008 Interna- tional Conference on Computational Intelligence for Modelling Control Automa- tion

Reference 8

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Observation 8b9976a4-4f52-4bd9-aa9d-cf85a28bd283 · outbound

This paper cites Mitigating Tail Narrowing in LLM Self-Improvement via Socratic-Guided Sampling.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Mitigating Tail Narrowing in LLM Self-Improvement via Socratic-Guided Sampling

Reference 9

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Observation f00bda77-aa71-440a-8c60-b776ea5265cf · outbound

This paper cites arXiv preprint arXiv:2407.06153 (2024).

Improving RL Exploration for LLM Reasoning through Retrospective Replay arXiv preprint arXiv:2407.06153 (2024)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:27.696732Z

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Observation ae96fd29-0008-44bd-beab-b6cc578ff7bf · outbound

This paper cites In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Reference 11

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Observation ce400777-20f3-462d-ac3f-b7f3fcd0fb7a · outbound

This paper cites MetaRM: Shifted Distributions Alignment via Meta-Learning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay MetaRM: Shifted Distributions Alignment via Meta-Learning

Reference 12

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Observation 03c2a41e-5bc4-4e4c-a7df-49adf5076bd3 · outbound

This paper cites Towards Understanding the Capability of Large Language Models on Code Clone Detection: A Survey.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Towards Understanding the Capability of Large Language Models on Code Clone Detection: A Survey

Reference 13

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Observation c00eeada-e0ed-49f8-86fe-a6ec1ce69bcc · outbound

This paper cites arXiv preprint arXiv:2506.02672 (2025).

Improving RL Exploration for LLM Reasoning through Retrospective Replay arXiv preprint arXiv:2506.02672 (2025)

Reference 14

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Observation 3ded2841-43b0-4cf3-9a7e-c520a900f59e · outbound

This paper cites In: Proceedings of the 62nd Annual Meeting of the AssociationforComputationalLinguistics(Volume1:LongPapers).pp.1932–1945 (2024).

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: Proceedings of the 62nd Annual Meeting of the AssociationforComputationalLinguistics(Volume1:LongPapers).pp.1932–1945 (2024)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:30.288728Z

Source-reported events for the cited work

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Observation a4f13fcd-9947-40fd-92d0-73e41fcf66b6 · outbound

This paper cites Nature590, 580 – 586 (2020),https://api.semanticscholar.org/ CorpusID:216552951.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Nature590, 580 – 586 (2020),https://api.semanticscholar.org/ CorpusID:216552951

Reference 16

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 265801ab-340f-4118-a497-9cccdf90e407 · outbound

This paper cites In: Proceedings of the 41st International Conference on Machine Learning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: Proceedings of the 41st International Conference on Machine Learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:30.231147Z

Source-reported events for the cited work

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Observation b5a32ec2-5821-47b7-bbf0-a158e84ef373 · outbound

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

Improving RL Exploration for LLM Reasoning through Retrospective Replay DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 18

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Observation eefee861-05aa-4a28-b84a-77bf10127813 · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Unresolved cited work

Reference 19

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Observation 48a7c01a-d34b-4642-a506-bddcf65291cd · outbound

This paper cites In: Vanschoren, J., Yeung, S.

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: Vanschoren, J., Yeung, S

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:30.118878Z

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Observation 7b9dcbfb-6158-4163-9e86-7b9800b51638 · outbound

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

Improving RL Exploration for LLM Reasoning through Retrospective Replay Measuring Mathematical Problem Solving With the MATH Dataset

Reference 21

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Observation 9055ac67-6aae-419c-95a0-8be5bed2262c · outbound

This paper cites Towards Reasoning in Large Language Models: A Survey.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Towards Reasoning in Large Language Models: A Survey

Reference 22

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Observation 7a2d2248-5edb-4f01-a135-7b470cc0818d · outbound

This paper cites RATIONALYST: Mining Implicit Rationales for Process Supervision of Reasoning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay RATIONALYST: Mining Implicit Rationales for Process Supervision of Reasoning

Reference 23

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Observation 2e2a4f09-b6db-4598-92c3-e9807baa9d1a · outbound

This paper cites Understanding the Effects of RLHF on LLM Generalisation and Diversity.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Understanding the Effects of RLHF on LLM Generalisation and Diversity

Reference 24

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Observation 25a5fd15-d033-42ca-bac4-4b1d4b32e08d · outbound

This paper cites LLM Post-Training: A Deep Dive into Reasoning Large Language Models.

Improving RL Exploration for LLM Reasoning through Retrospective Replay LLM Post-Training: A Deep Dive into Reasoning Large Language Models

Reference 25

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Observation b9c4d114-ae70-4143-b99d-e46c18016fa9 · outbound

This paper cites Information Fusion85, 1–22 (2022).

Improving RL Exploration for LLM Reasoning through Retrospective Replay Information Fusion85, 1–22 (2022)

Reference 26

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Observation 1896f1dd-c6fb-48f3-b105-f6967430cbcd · outbound

This paper cites StarCoder: may the source be with you!.

Improving RL Exploration for LLM Reasoning through Retrospective Replay StarCoder: may the source be with you!

Reference 27

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Observation f60984d5-12cf-40a0-889c-d2d0327c1bd5 · outbound

This paper cites Deep Reinforcement Learning: An Overview.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Deep Reinforcement Learning: An Overview

Reference 28

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Observation d67fe6a5-165f-4abe-981a-cdc3bc643bc2 · outbound

This paper cites RLTF: Reinforcement Learning from Unit Test Feedback.

Improving RL Exploration for LLM Reasoning through Retrospective Replay RLTF: Reinforcement Learning from Unit Test Feedback

Reference 29

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Observation b834e9ad-e8c2-4d10-8381-da9a0ba90d6f · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 30

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Observation 4196ed8a-44ca-45b0-8c1b-b0e3c47716de · outbound

This paper cites Brief analysis of DeepSeek R1 and its implications for Generative AI.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Brief analysis of DeepSeek R1 and its implications for Generative AI

Reference 31

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Observation ec987063-8bc8-4f1c-8f08-1107e78c04e4 · outbound

This paper cites In: 2018 IEEE Inter- national Conference on Robotics and Automation (ICRA).

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: 2018 IEEE Inter- national Conference on Robotics and Automation (ICRA)

Reference 32

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Observation b74eb59b-54e3-4ada-ae5b-0b7b012fce14 · outbound

This paper cites arXiv preprint arXiv:2407.11511 (2024).

Improving RL Exploration for LLM Reasoning through Retrospective Replay arXiv preprint arXiv:2407.11511 (2024)

Reference 33

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Observation de719de5-add6-4a7a-aa2d-16575cc7cd27 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Code Llama: Open Foundation Models for Code

Reference 34

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Observation 98c32d55-ab36-466a-a87f-bc3f7c533e1b · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Prioritized Experience Replay

Reference 35

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Observation 667eed7b-7bc1-4c79-9e4e-437d47d7f5e1 · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 36

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Observation 52cc8e12-af0e-4e6a-b088-e953c55ea7b2 · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Proximal Policy Optimization Algorithms

Reference 37

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This paper cites 5-thinking: Advancing superb reasoning models with reinforcement learning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay 5-thinking: Advancing superb reasoning models with reinforcement learning

Reference 38

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Observation f4bc0226-3566-42ed-aba4-52742dfa2fda · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 39

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Observation f232fc04-9978-43c8-8f7e-0226eb9bcb16 · outbound

This paper cites In: The 2023 Conference on Empirical Methods in Natural Language Processing.

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: The 2023 Conference on Empirical Methods in Natural Language Processing

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:30.101836Z

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Observation dfe5a085-9bf6-49bb-bcf9-4e0876a6106a · outbound

This paper cites Execution-based Code Generation using Deep Reinforcement Learning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Execution-based Code Generation using Deep Reinforcement Learning

Reference 41

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Observation 85e0fc10-7300-46e5-98b4-581cc48cf3a4 · outbound

This paper cites Advances in neural informa- tion processing systems12 (1999).

Improving RL Exploration for LLM Reasoning through Retrospective Replay Advances in neural informa- tion processing systems12 (1999)

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:30.047980Z

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Observation 562cef5c-f270-45ac-8046-207313ef9b73 · outbound

This paper cites Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.697223Z

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Observation 32e0b9d7-d87f-4c01-975a-4981ca8b7e02 · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Unresolved cited work

Reference 44

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Observation 32f7067e-076a-4510-b437-f9e204aa0d67 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.707518Z

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Solving math word problems with process- and outcome-based feedback

Reference 46

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.737965Z

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.847092Z

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Observation 28577e6f-3437-4add-90e9-300765c13701 · outbound

This paper cites Machine learning8, 229–256 (1992).

Improving RL Exploration for LLM Reasoning through Retrospective Replay Machine learning8, 229–256 (1992)

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.851183Z

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Progressive Mastery: Customized Curriculum Learning with Guided Prompting for Mathematical Reasoning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.855634Z

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Observation a571a8ea-e785-4453-ad81-2414c8c6a3d3 · outbound

This paper cites In: International Conference on Machine Learning.

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: International Conference on Machine Learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:29.883416Z

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Observation a016837c-4a05-42e1-b30e-e793c6fd24c5 · outbound

This paper cites Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain.

Improving RL Exploration for LLM Reasoning through Retrospective Replay Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.864222Z

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Observation ede8af13-74e9-4136-b940-c3d979966938 · outbound

This paper cites arXiv preprint arXiv:2505.17793 (2025).

Improving RL Exploration for LLM Reasoning through Retrospective Replay arXiv preprint arXiv:2505.17793 (2025)

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.869017Z

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Observation 455a8c2b-08a9-48e3-9529-729c736bc6d6 · outbound

This paper cites A Deeper Look at Experience Replay.

Improving RL Exploration for LLM Reasoning through Retrospective Replay A Deeper Look at Experience Replay

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T11:53:28.872617Z

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Observation bff13c8d-45e2-4636-a8c6-262d0a021569 · outbound

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Improving RL Exploration for LLM Reasoning through Retrospective Replay Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:53:29.872604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6421c666-6154-4714-ba74-d565060ac54b · outbound

This paper cites In: NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following (2023).

Improving RL Exploration for LLM Reasoning through Retrospective Replay In: NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following (2023)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:53:29.859319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation a57d2fe3-68d0-4906-9adc-01e65938bc09 · inbound

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning cites this paper.

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning Improving RL Exploration for LLM Reasoning through Retrospective Replay

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T18:30:38.055667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 331e8f51-bedd-44b1-8469-cd6695202c97 · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Improving RL Exploration for LLM Reasoning through Retrospective Replay

Reference 118

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:02:25.295695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8d570112-a7fc-4c0c-84ae-491828bceca0 · inbound

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning cites this paper.

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning Improving RL Exploration for LLM Reasoning through Retrospective Replay

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:56:12.821899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0d92ba2d-2def-4264-a3d6-9daafaa5fb0a · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Improving RL Exploration for LLM Reasoning through Retrospective Replay

Reference 266

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T20:56:13.562994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f71fc0eb-23d5-43eb-abf0-9f60c6da2b44 · inbound

Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR cites this paper.

Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR Improving RL Exploration for LLM Reasoning through Retrospective Replay

Reference 101

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:36:25.167562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f3695488-aca2-48e0-b879-1b07bbbd95a5 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning Improving RL Exploration for LLM Reasoning through Retrospective Replay

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:40.190471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.