🧑‍🔬 Who cites Adam Zsolt Wagner

201 citations of their works from 190 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · ← Adam Zsolt Wagner

1. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 216 citations
2. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
3. Darwin Godel Machine: Open-Ended Evolution of Self-Improving AgentsarXiv:2505.22954Jenny Zhang, Shengran Hu, Cong Lu, et al.2025 · 47 citations
4. ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program EvolutionarXiv:2509.19349Robert Tjarko Lange, Yuki Imajuku, Edoardo Cetin2025 · 42 citations
5. A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super IntelligencearXiv:2507.21046Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.2025 · 36 citations
6. An AI system to help scientists write expert-level empirical softwareNatureEser Aygün, Anastasiya Belyaeva, Gheorghe Comanici, et al.2025 · 27 citations
7. ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task DecompositionarXiv:2503.21248Yujie Liu, Zonglin Yang, Tong Xie, et al.2025 · 25 citations
8. Towards Scientific Intelligence: A Survey of LLM-based Scientific AgentsarXiv:2503.24047Shuo Ren, Can Xie, Pu Jian, et al.2025 · 24 citations
9. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
10. 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
11. The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research IdeasarXiv:2506.20803Chenglei Si, Tatsunori Hashimoto, Diyi Yang2025 · 19 citations
12. DeepScientist: Advancing Frontier-Pushing Scientific Findings ProgressivelyarXiv:2509.26603Yixuan Weng, Minjun Zhu, Qiujie Xie, et al.2025 · 17 citations
13. Mathematical exploration and discovery at scalearXiv:2511.02864Bogdan Georgiev, Javier Gómez-Serrano, Terence Tao, et al.2025 · 16 citations
14. ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific WorkflowsarXiv:2505.19897Qiushi Sun, Zhoumianze Liu, Chang Ma, et al.2025 · 11 citations
15. CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended DiscoveryarXiv:2604.01658Ao Qu, Han Zheng, Zijian Zhou, et al.2026 · 9 citations
16. Reinforcement Learning for Self-Improving Agent with Skill LibraryAnnual Meeting of the Association for Computational Linguistics (ACL)Jiongxiao Wang, Qiaojing Yan, Yawei Wang, et al.2026 · 8 citations
17. AlphaGo Moment for Model Architecture DiscoveryarXiv:2507.18074Yixiu Liu, Yang Nan, Weixian Xu, et al.2025 · 8 citations
18. CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving ChallengesFindings of the Association for Computational LinguisticsZihan Wang, Lam Nguyen, Zhengyang Zhao, et al.2026 · 6 citations
19. Training AI Co-Scientists Using Rubric RewardsarXiv:2512.23707Shashwat Goel, Rishi Hazra, Dulhan Jayalath, et al.2025 · 6 citations
20. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
21. AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model DiscoveryarXiv:2604.05550Yu Li, Chenyang Shao, Xinyang Liu, et al.2026 · 5 citations
22. AlphaResearch: Accelerating New Algorithm Discovery with Language ModelsarXiv:2511.08522Zhaojian Yu, Kaiyue Feng, Yilun Zhao, et al.2025 · 3 citations
23. Can We Predict Before Executing Machine Learning Agents?Annual Meeting of the Association for Computational Linguistics (ACL)Jingsheng Zheng, Jintian Zhang, Yujie Luo, et al.2026 · 2 citations
24. Training AI Scientists to Replicate ResearcharXiv:2608.13331Damon Falck, Samer Sabri, Anja Surina, et al.2026 · 2 citations
25. Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the FutureAnnual Meeting of the Association for Computational Linguistics (ACL)Sihong Wu, Owen Jiang, Yilun Zhao, et al.2026 · 1 citation
26. 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
27. Workflow Closure Is Not Scientific Closure in Auto-Research SystemsarXiv:2605.26200Shuai Wang, Xinyuan Tian, Pangpang Liu, et al.2026 · 1 citation
28. AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model SelectionFindings of the Association for Computational LinguisticsPretam Ray, Pratik Prabhanjan Brahma, Zicheng Liu, et al.2026
29. AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and ReuseAnnual Meeting of the Association for Computational Linguistics (ACL)Zhang Zhang, Shuqi Lu, Hongjin Qian, et al.2026
30. AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity AssessmentAnnual Meeting of the Association for Computational Linguistics (ACL)Yixuan Wang, Yue Huang, Hong Qian, et al.2026
31. Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based OptimizersConference of the European Chapter of the Association for Computational Linguistics (EACL)Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.2026
32. Auditing Discovery Claims: A Two-Sided Criterion for Agentic Science, with the Negative Side DecidablearXiv:2608.00981Wenhui Chen, Jianlin Chen, Ziyao Lin, et al.2026
33. Demystify the Role of Memory in Machine Learning Engineering AgentsFindings of the Association for Computational LinguisticsXinyu Zhao, Junpeng Wang, Yuzhong Chen, et al.2026
34. Evolutionary Search for Automated Design of Uncertainty Quantification MethodsAnnual Meeting of the Association for Computational Linguistics (ACL)Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.2026
35. Open Problems Solved by LLMs? A Survey of Verifiable Mathematical DiscoveryBig Picture v2: Crafting a Research NarrativeIoannis Tzachristas, Georgios Tzachristas, Aifen Sui2026
36. Output-Space Search: Targeting LLM Generations in a Frozen Encoder-Defined Output SpaceWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraTobias Materzok2026

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