AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning | Paper Citation Record

Observation 82d516c7-7361-4464-8e74-9c0c1715ae86 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 1

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Observation 9b876981-78b5-410b-af7a-3a85d061131b · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

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Observation 942e9632-ec05-48bf-9c02-77f51e92b41e · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 3

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Observation 39cb9bad-9b74-4640-8722-3fa2f343bdf6 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 4

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 5

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Observation 7d3d36e5-cd90-433b-bacb-6f821ec383a5 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 6

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Observation 38f9310c-887e-4e49-82dc-a9f20ac46ec1 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 7

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Observation e7c5d4b0-11bd-4d90-8efc-386bb35b325f · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 8

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Observation b38d946d-e347-49ed-9f92-f7c6a045cff9 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 9

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Observation f6aa2346-0797-4f1c-b7eb-0d3b0690e0f3 · outbound

This paper cites The eleventh international conference on learning representations , year=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning The eleventh international conference on learning representations , year=

Reference 10

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Observation 46fbc3ad-f81c-4ce0-a59e-7e629cc2bcbf · outbound

This paper cites ALFWorld: Aligning Text and Embodied Environments for Interactive Learning.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

Reference 11

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Observation 93c6b923-0541-4cbf-8dfc-cf2d80c5f27a · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 12

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Observation 80ccb4e7-5879-4ca6-8af8-86c1b2414914 · outbound

This paper cites Transactions of the Association for Computational Linguistics , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Transactions of the Association for Computational Linguistics , volume=

Reference 13

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Observation 05607002-a70e-44f7-bb3e-313b32897772 · outbound

This paper cites Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 14

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Observation 9f802145-6ca0-4ede-bc71-aefee01ef16d · outbound

This paper cites Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=

Reference 15

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Observation baa8d1cd-9425-4610-b82a-e6bbd84bca61 · outbound

This paper cites Proceedings of the 2018 conference on empirical methods in natural language processing , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the 2018 conference on empirical methods in natural language processing , pages=

Reference 16

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Observation e5af50b8-21fb-4128-b71b-c30f7aa8743c · outbound

This paper cites Proceedings of the 28th International Conference on Computational Linguistics , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the 28th International Conference on Computational Linguistics , pages=

Reference 17

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Observation 38266335-f39a-499d-9c1c-93407a11ae7a · outbound

This paper cites Transactions of the Association for Computational Linguistics , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Transactions of the Association for Computational Linguistics , volume=

Reference 18

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Observation 47c397c8-2827-4ea1-97a6-b37411405097 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.391568Z

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Observation 59f97e98-7067-418a-9b87-e5456bdee721 · outbound

This paper cites Group-in-Group Policy Optimization for LLM Agent Training.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Group-in-Group Policy Optimization for LLM Agent Training

Reference 20

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Observation 0799257c-2fd8-465b-8d62-1b94be6143c5 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 21

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Observation e19984f0-4bd1-49d2-a2f6-1f328b391069 · outbound

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

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 22

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Observation 19a84209-762e-4208-8078-1552acbeca38 · outbound

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

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 23

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Observation ed2c257f-72f6-4040-8532-4305bb8a4b74 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.424814Z

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Observation 435bca4a-1b8b-4bbf-babb-8c9198a3daf4 · outbound

This paper cites an unresolved cited work.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Unresolved cited work

Reference 25

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Observation 9b77dde9-97cb-4019-9b5b-082451aeb98a · outbound

This paper cites Qwen3 Technical Report.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Qwen3 Technical Report

Reference 26

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Observation d481ff67-37a9-46e6-9107-65384b2c8bc8 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Kimi K2: Open Agentic Intelligence

Reference 27

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Observation 3763a7ad-38f7-4568-ae6b-fe66c08fd348 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 28

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Observation c197bb77-bb0a-48d7-9159-3b7a12768644 · outbound

This paper cites Proceedings of the ACM on Web Conference 2025 , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the ACM on Web Conference 2025 , pages=

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:53:28.850775Z

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Observation bbbdf02e-35a0-456f-8d4c-fce5ee880c45 · outbound

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

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 30

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Observation 4862341c-860a-4872-984e-94d3f753b5e5 · outbound

This paper cites arXiv preprint arXiv:2601.16725 , year=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning arXiv preprint arXiv:2601.16725 , year=

Reference 31

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Observation 3057d07f-715f-4706-a0eb-4d67daca02a5 · outbound

This paper cites GPT-4o System Card.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning GPT-4o System Card

Reference 32

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This paper cites Advances in Neural Information Processing Systems , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 33

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This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 34

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Observation dc2c9a41-6e4e-4169-98b9-6e3b1d2631e2 · outbound

This paper cites Agentic Reinforced Policy Optimization.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Agentic Reinforced Policy Optimization

Reference 35

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 36

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 37

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 38

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 39

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 40

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This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 41

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Observation d506fd67-ed4c-452e-9700-251ccf57922a · outbound

This paper cites 2023 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2023 , eprint=

Reference 42

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AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2011 , eprint=

Reference 43

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Observation 9d9835cf-a47d-46c9-a800-00dddecdce5e · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 44

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Observation 51d3c44d-c768-4c71-8091-f0dc1852d21d · outbound

This paper cites 2019 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2019 , eprint=

Reference 45

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Observation 26c3af54-464c-4908-9818-21de4473cd16 · outbound

This paper cites Mobile-Agent-v3: Fundamental Agents for GUI Automation.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Mobile-Agent-v3: Fundamental Agents for GUI Automation

Reference 46

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Observation 69b7dcf3-89c5-4f58-878c-33c07661a583 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 47

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Observation d0db4c0b-5dc5-4c92-861a-cdd6372cfdf0 · outbound

This paper cites 2024 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2024 , eprint=

Reference 48

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Observation eee1988e-068f-45b6-b20e-d4002c8314f8 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 49

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Observation 97c813f3-7da2-420d-a63b-8389b4d8abb0 · outbound

This paper cites 2023 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2023 , eprint=

Reference 50

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Observation 53474c2f-3fdb-4541-b82d-b9b86cbf9833 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 51

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Observation 3236c731-949b-4c7e-9279-ebe740505a87 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 52

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Observation d6c29359-0c29-4e01-a06c-fa5bb5030e1f · outbound

This paper cites arXiv preprint arXiv:2602.03048 , year=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning arXiv preprint arXiv:2602.03048 , year=

Reference 53

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Observation c9e66127-70dc-4a95-9552-615c82320dc8 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 54

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Observation 21728072-1869-488f-9096-e1cef7744cfa · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 55

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Observation 34ea40fb-8d47-4cd8-9d2d-bbc6dac40c63 · outbound

This paper cites 2026 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2026 , eprint=

Reference 56

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Observation 9808c1ba-c370-49b1-9be9-5c1f14521c1d · outbound

This paper cites 2017 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2017 , eprint=

Reference 57

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Observation af5e4c2e-d7f3-4cad-b2d3-cda22e9a7338 · outbound

This paper cites 2016 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2016 , eprint=

Reference 58

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Observation 571504e8-9896-4662-9772-a7c3a091c430 · outbound

This paper cites 2019 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2019 , eprint=

Reference 59

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Observation a7b45576-74ae-44ce-9fa0-e0d633787833 · outbound

This paper cites 2024 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2024 , eprint=

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:53:28.134605Z

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Observation d362eef3-4808-431e-8529-c8335ed30d54 · outbound

This paper cites 2025 , eprint=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning 2025 , eprint=

Reference 61

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Observation 3bc4c876-61cf-4ab1-a78b-c0ae6c7cb9d3 · outbound

This paper cites Journal of the American Statistical Association , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Journal of the American Statistical Association , volume=

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:53:28.107894Z

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.

Observation cbb49228-4cbd-44e1-b1c6-5957ad50e682 · outbound

This paper cites The Annals of Mathematical Statistics , volume=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning The Annals of Mathematical Statistics , volume=

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:53:28.091321Z

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.

Observation 0c69cbd7-d25b-445e-a4ff-0cc00bd9f76b · outbound

This paper cites SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.906690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f139449b-87b8-44c3-8130-b16a48d37b81 · outbound

This paper cites OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning

Reference 65

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T19:53:27.087135Z

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.

Observation 711881f7-a651-4888-8f97-894bf50f5a8a · outbound

This paper cites SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution

Reference 66

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T19:53:27.063688Z

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.

Observation 2822f740-672d-41cc-8588-6f1dfa8c2170 · outbound

This paper cites Self-Distilled Agentic Reinforcement Learning.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Self-Distilled Agentic Reinforcement Learning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.921007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe8762e6-3bb4-47ce-b6a6-1854bb9d4d11 · outbound

This paper cites Artificial Intelligence , volume =.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Artificial Intelligence , volume =

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.926059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 320f4540-0391-40a4-9ae5-48be7875b92c · outbound

This paper cites Journal of Mathematical Analysis and Applications , volume =.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Journal of Mathematical Analysis and Applications , volume =

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:53:28.062099Z

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.

Observation 9a0b8028-fd40-4eb3-8fe3-a26b2292cfc6 · outbound

This paper cites arXiv preprint arXiv:2602.07594 , year=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning arXiv preprint arXiv:2602.07594 , year=

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.935615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe176c02-ad4a-4efa-b45b-4c78bc7b7dff · outbound

This paper cites Look Before You Leap: Autonomous Exploration for LLM Agents.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Look Before You Leap: Autonomous Exploration for LLM Agents

Reference 71

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T19:53:26.818924Z

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.

Observation c41e9e68-7cc8-458d-8f78-953acbafccda · outbound

This paper cites arXiv preprint arXiv:2601.14050 , year=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning arXiv preprint arXiv:2601.14050 , year=

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:25.959586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1c9e453-598e-4be7-979c-de5c7e49473d · outbound

This paper cites Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts

Reference 73

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T19:53:26.507641Z

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.

Observation 81cb3325-a230-4c30-89de-3c6bf51209f1 · outbound

This paper cites Memento: Fine-tuning LLM Agents without Fine-tuning LLMs.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:26.038845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2972291e-fd12-47ea-83e2-d0fd5007ea01 · outbound

This paper cites Reducing Tool Hallucination via Reliability Alignment.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Reducing Tool Hallucination via Reliability Alignment

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:26.084902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d28bd039-8e3e-45fc-a621-9b7d51d947a0 · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:26.141889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f511aa7-b0b0-485b-993e-0790a83398b0 · outbound

This paper cites arXiv preprint arXiv:2509.11543 , year=.

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning arXiv preprint arXiv:2509.11543 , year=

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T19:53:26.173725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

Outbound references

Pith citing papers