🧑‍🔬 Who cites Quentin Carbonneaux

105 citations of their works from 98 papers of our library (of the 149,439 whose bibliographies we read) · 33 with a page here, the most cited first · ← Quentin Carbonneaux

1. DAPO: An Open-Source LLM Reinforcement Learning System at ScalearXiv:2503.14476Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.2025 · 668 citations
2. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
3. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
4. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
5. TTRL: Test-Time Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.2025 · 76 citations
6. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
7. Group-in-Group Policy Optimization for LLM Agent TrainingConference on Neural Information Processing Systems (NeurIPS)Lang Feng, Zhenghai Xue, Tingcong Liu, et al.2025 · 69 citations
8. Kevin: Multi-Turn RL for Generating CUDA KernelsarXiv 2025Carlo Baronio, Pietro Marsella, Ben Pan, et al.2025 · 69 citations
9. SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software EvolutionConference on Neural Information Processing Systems (NeurIPS)Yuxiang Wei, Olivier Duchenne, Jade Copet, et al.2025 · 64 citations
10. WebDancer: Towards Autonomous Information Seeking AgencyConference on Neural Information Processing Systems (NeurIPS)Jialong Wu, Baixuan Li, Runnan Fang, et al.2025 · 50 citations
11. SelfCodeAlign: Self-Alignment for Code GenerationConference on Neural Information Processing Systems (NeurIPS)Yuxiang Wei, Federico Cassano, Jiawei Liu, et al.2024 · 32 citations
12. Online Difficulty Filtering for Reasoning Oriented Reinforcement LearningConference of the European Chapter of the Association for Computational Linguistics (EACL)Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.2026 · 22 citations
13. A Survey of Post-Training Scaling in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hanyu Lai, Xiao Liu, Junjie Gao, et al.2025 · 18 citations
14. Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy DistillationarXiv:2603.19220Zhuolin Yang, Zihan Liu, Yang Chen, et al.2026 · 16 citations
15. 100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language ModelsarXiv:2505.00551Chong Zhang, Yue Deng, Xiang Lin, et al.2025 · 9 citations
16. Problem Solving Through Human–AI Preference-based CooperationComputational LinguisticsSubhabrata Dutta, Timo Kaufmann, Goran Glavaš, et al.2025 · 9 citations
17. From Completion to Editing: Unlocking Context-Aware Code Infilling via Search-and-Replace Instruction TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Jiajun Zhang, Zeyu Cui, Jiaxi Yang, et al.2026 · 6 citations
18. DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree TraversalAnnual Meeting of the Association for Computational Linguistics (ACL)Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, et al.2025 · 4 citations
19. Kimi-Dev: Agentless Training as Skill Prior for SWE-AgentsarXiv:2509.23045Zonghan Yang, Shengjie Wang, Kelin Fu, et al.2025 · 4 citations
20. Agentic Rubrics as Contextual Verifiers for SWE AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Mohit Raghavendra, Anisha Gunjal, Bing Liu, et al.2026 · 3 citations
21. Behavior Knowledge Merge in Reinforced Agentic ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiangchi Yuan, Dachuan Shi, Chunhui Zhang, et al.2026 · 3 citations
22. 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
23. CIS-RG at QIAS 2025 Shared Task: Approaches for Enhancing Performance of LLM on Islamic Legal Reasoning and its Mathematical CalculationsArabic Natural Language Processing Conference (ArabicNLP)Farouk Zaki, Osama2025 · 2 citations
24. Energy Matching based Preference Learning for Diffusion Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Shiv Shankar2026 · 1 citation
25. GAPO: Robust Advantage Estimation for Real-World Code LLMsFindings of the Association for Computational LinguisticsJianqing Zhang, Zhezheng Hao, Wei Xia, et al.2026 · 1 citation
26. SeCuRepair: Semantics-Aligned, Curriculum-Driven, and Reasoning-Enhanced Vulnerability Repair FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Chengran Yang, Ting Zhang, Jinfeng Jiang, et al.2026 · 1 citation
27. Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-VisualizationConference of the European Chapter of the Association for Computational Linguistics (EACL)Mizanur Rahman, Mohammed Saidul Islam, Md Tahmid Rahman Laskar, et al.2026
28. CodeRM-NT: Reward Model for Code RL without Unit TestsFindings of the Association for Computational LinguisticsXiao Xia, Dan Zhang, Tianrui Sun2026
29. Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse DomainsAnnual Meeting of the Association for Computational Linguistics (ACL)Yi Su, Dian Yu, Linfeng Song, et al.2026
30. Curing Miracle Steps in LLM Mathematical Reasoning with Rubric RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.2026
31. Generalizable LLM Learning of Graph Synthetic Data with Post-training AlignmentFindings of the Association for Computational LinguisticsYizhuo Zhang, Heng Wang, Shangbin Feng, et al.2026
32. Tailored Primitive Initialization is the Secret Key to Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yihang Yao, Guangtao Zeng, Raina Wu, et al.2026
33. When “Correct” Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?Annual Meeting of the Association for Computational Linguistics (ACL)Yibo Peng, James Song, Lei Li, et al.2026

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