🔗 Who cites «Training Software Engineering Agents and Verifiers with SWE-Gym»

71 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · ← back to «Training Software Engineering Agents and Verifiers with SWE-Gym»

1. 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
2. APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human InterplayConference on Neural Information Processing Systems (NeurIPS)Akshara Prabhakar, Zuxin Liu, Ming Zhu, et al.2025 · 36 citations
3. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
4. UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement LearningarXiv:2509.02544Haoming Wang, Haoyang Zou, Huatong Song, et al.2025 · 26 citations
5. A Survey on Evaluation of LLM-based AgentsFindings of the Association for Computational LinguisticsAsaf Yehudai, Lilach Eden, Alan Li, et al.2026 · 21 citations
6. 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
7. Qwen3-Coder-Next Technical ReportarXiv:2603.00729Ruisheng Cao, Mouxiang Chen, Jiawei Chen, et al.2026 · 15 citations
8. 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
9. Kimi-Dev: Agentless Training as Skill Prior for SWE-AgentsarXiv:2509.23045Zonghan Yang, Shengjie Wang, Kelin Fu, et al.2025 · 4 citations
10. 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
11. Skywork-SWE: Unveiling Data Scaling Laws for Software Engineering in LLMsarXiv:2506.19290Liang Zeng, Yongcong Li, Yuzhen Xiao, et al.2025 · 3 citations
12. POSTCONDBENCH: Benchmarking Correctness and Completeness in Formal Postcondition InferenceFindings of the Association for Computational LinguisticsGehao Zhang, Juan Zhai2026 · 1 citation
13. AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiheng Xi, Dingwen Yang, Jiaqi Liu, et al.2026
14. Beyond the Context Window: Scaling Agentic RL via End-to-end Optimized Context CompressionAnnual Meeting of the Association for Computational Linguistics (ACL)Miao Lu, Weiwei Sun, Weihua Du, et al.2026
15. EGSS: Entropy-guided Stepwise Scaling for Reliable Software EngineeringAnnual Meeting of the Association for Computational Linguistics (ACL)Chenhui Mao, Yuanting Lei, Zhixiang Wei, et al.2026
16. Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model FactualityFindings of the Association for Computational LinguisticsMike Zhang, Johannes Bjerva, Russa Biswas2026
17. 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
18. 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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