🔗 Who cites «IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization»

14 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization»

1. 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
2. Internal Chain-of-Thought: Empirical Evidence for Layer-wise Subtask Scheduling in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhipeng Yang, Junzhuo Li, Siyu Xia, et al.2025 · 7 citations
3. 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
4. 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
5. 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
6. IF-RewardBench: Benchmarking Judge Models for Instruction-Following EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Bosi Wen, Yilin Niu, Cunxiang Wang, et al.2026 · 1 citation

8 more papers of our library cite it; they have no page here yet.

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