🧑‍🔬 Who cites Huan-ang Gao

91 citations of their works from 91 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · ← Huan-ang Gao

1. A Survey of On-Policy Distillation for Large Language ModelsarXiv:2604.00626Mingyang Song, Mao Zheng2026 · 41 citations
2. Revisiting On-Policy Distillation: Empirical Failure Modes and Simple FixesarXiv:2603.25562Yuqian Fu, Haohuan Huang, Kaiwen Jiang, et al.2026 · 31 citations
3. From AI for Science to Agentic Science: A Survey on Autonomous Scientific DiscoveryarXiv:2508.14111Jiaqi Wei, Yuejin Yang, Xiang Zhang, et al.2025 · 19 citations
4. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
5. EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific DiscoveryarXiv:2603.08127Yougang Lyu, Xi Zhang, Xinhao Yi, et al.2026 · 10 citations
6. Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy DistillationarXiv:2604.13010Yecheng Wu, Song Han, Han Cai2026 · 10 citations
7. CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended DiscoveryarXiv:2604.01658Ao Qu, Han Zheng, Zijian Zhou, et al.2026 · 9 citations
8. KL for a KL: On-Policy Distillation with Control Variate BaselinearXiv:2605.07865Minjae Oh, Sangjun Song, Gyubin Choi, et al.2026 · 8 citations
9. Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and WhyarXiv:2605.10889Mohammadreza Armandpour, Fatih Ilhan, David Harrison, et al.2026 · 7 citations
10. Asymmetric On-Policy Distillation: Bridging Exploitation and Imitation at the Token LevelarXiv:2605.06387Nan Jia, Haojin Yang, Xing Ma, et al.2026 · 6 citations
11. Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective RecipearXiv:2605.03677Wenjin Hou, Shangpin Peng, Weinong Wang, et al.2026 · 6 citations
12. Mem²Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Zihao Cheng, Zeming Liu, Yingyu Shan, et al.2026 · 5 citations
13. MemoBrain: Executive Memory as an Agentic Brain for ReasoningFindings of the Association for Computational LinguisticsHongjin Qian, Zhao Cao, Zheng Liu2026 · 1 citation
14. On Safety Risks in Experience-Driven Self-Evolving AgentsFindings of the Association for Computational LinguisticsWeixiang Zhao, Yichen Zhang, Yingshuo Wang, et al.2026 · 1 citation
15. What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary SearchFindings of the Association for Computational LinguisticsXinhao Zhang, Xi Chen, François Portet, et al.2026 · 1 citation
16. A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and SolutionsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.2026
17. Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual LearningFindings of the Association for Computational LinguisticsZheng Wu, Xingyu Lou, Xinbei Ma, et al.2026
18. GUI0: Self-Evolving Foundational GUI Agents in Super App EcosystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyi Wang, Wei Dai, Kyle Qiao, et al.2026
19. Self-Sum: Teaching an Agent to Decide Itself When and What to SummarizeFindings of the Association for Computational LinguisticsHongru Wang, Rui Wang, Jushi Kai, et al.2026
20. Towards Self-Evolving Agents: Enabling Autonomy through Interactive Experience RefinementFindings of the Association for Computational LinguisticsCheng Yang, Xuemeng Yang, Licheng Wen, et al.2026

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