Who cites «Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models»
- Kimi K2: Open Agentic IntelligencearXiv:2507.20534Kimi Team, Yifan Bai, Yiping Bao, et al.2025 · 347 citations
- Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
- FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation ResearcharXiv:2405.13576Jiajie Jin, Yutao Zhu, Guanting Dong, et al.2024 · 77 citations
- WebThinker: Empowering Large Reasoning Models with Deep Research CapabilityConference on Neural Information Processing Systems (NeurIPS)Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.2025 · 72 citations
- Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
- We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?arXiv:2407.01284Runqi Qiao, Qiuna Tan, Guanting Dong, et al.2024 · 65 citations
- Checklists Are Better Than Reward Models For Aligning Language ModelsConference on Neural Information Processing Systems (NeurIPS)Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.2025 · 37 citations
- Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning PerspectivearXiv:2412.14135Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2024 · 33 citations
- CFBench: A Comprehensive Constraints-Following Benchmark for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Tao Zhang, ChengLIn Zhu, Yanjun Shen, et al.2025 · 30 citations
- OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Tianci Liu, Ran Xu, Tony Yu, et al.2026 · 25 citations
- Hierarchical Document Refinement for Long-context Retrieval-augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Jiajie Jin, Xiaoxi Li, Guanting Dong, et al.2025 · 25 citations
- RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoxi Li, Jiajie Jin, Yujia Zhou, et al.2025 · 19 citations
- VerIF: Verification Engineering for Reinforcement Learning in Instruction FollowingConference on Empirical Methods in Natural Language Processing (EMNLP)Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.2025 · 18 citations
- RAG-Critic: Leveraging Automated Critic-Guided Agentic Workflow for Retrieval Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Jiajie Jin, Xiaoxi Li, et al.2025 · 14 citations
- Language Models can Self-Lengthen to Generate Long TextsarXiv:2410.23933Shanghaoran Quan, Tianyi Tang, Bowen Yu, et al.2024 · 13 citations
- Progressive Multimodal Reasoning via Active RetrievalAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.2025 · 10 citations
- UltraIF: Advancing Instruction Following from the WildConference on Empirical Methods in Natural Language Processing (EMNLP)Kaikai An, Li Sheng, Ganqu Cui, et al.2025 · 7 citations
- EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tao Zou, Xinghua Zhang, Haiyang Yu, et al.2025 · 5 citations
- Baichuan Alignment Technical ReportarXiv:2410.14940Mingan Lin, Fan Yang, Yanjun Shen, et al.2024 · 5 citations
- MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language ModelsFindings of the Association for Computational LinguisticsJunjie Ye, Caishuang Huang, Zhuohan Chen, et al.2026 · 4 citations
- MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Huang, Jiaheng Liu, Yancheng He, et al.2025 · 4 citations
- Instructions are all you need: Self-supervised Reinforcement Learning for Instruction FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Qingyu Ren, Qianyu He, Powei Chang, et al.2026 · 3 citations
- IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Bosi Wen, Yilin Niu, Cunxiang Wang, et al.2026 · 1 citation
- Reasoning Up the Instruction Ladder for Controllable Language ModelsFindings of the Association for Computational LinguisticsZishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.2026 · 1 citation
- ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuancheng Yang, Lin Yang, Xu Wang, et al.2026
- PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.2026
- PRISM: Probabilistic Reward Model with Inherent Structural ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuhang Zhou, Yixin Cao, Yuchen Ni, et al.2026
- Sem-DPO: Mitigating Semantic Inconsistency in Preference Optimization for Prompt EngineeringFindings of the Association for Computational LinguisticsAnas Mohamed, Azal Ahmad Khan, Xinran Wang, et al.2026
- TinyJudge: Unverifiable Constraint Alignment via Lightweight Specialist EnsemblesAnnual Meeting of the Association for Computational Linguistics (ACL)Yirong Zeng, Yufei Liu, Xiao Ding, et al.2026
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