🔗 Who cites «Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models»

38 papers of our library cite it (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · ← back to «Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models»

1. LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMsarXiv:2408.07055Yushi Bai, Jiajie Zhang, Xin Lv, et al.2024 · 66 citations
2. 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
3. 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
4. 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
5. IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Xinghua Zhang, Haiyang Yu, Cheng Fu, et al.2025 · 14 citations
6. Pre-training Distillation for Large Language Models: A Design Space ExplorationAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Peng, Xin Lv, Yushi Bai, et al.2025 · 14 citations
7. 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
8. 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
9. Baichuan Alignment Technical ReportarXiv:2410.14940Mingan Lin, Fan Yang, Yanjun Shen, et al.2024 · 5 citations
10. 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
11. 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
12. 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
13. 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
14. DSMentor: Curriculum-Guided Inference with Online Memory for Data-Science LLM AgentsWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraHe Wang, Alexander Hanbo Li, Yiqun Hu, et al.2026
15. 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
16. 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

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

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