🧑‍🔬 Who cites Yunjia Qi

74 citations of their works from 72 papers of our library (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← Yunjia Qi

1. 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
2. Long-context LLMs Struggle with Long In-context LearningarXiv:2404.02060Tianle Li, Ge Zhang, Quy Duc Do, et al.2024 · 138 citations
3. LLMs Get Lost In Multi-Turn ConversationarXiv:2505.06120Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, et al.2025 · 82 citations
4. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
5. 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
6. 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
7. Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal UncertaintyFindings of the Association for Computational LinguisticsChao Xue, Yao Wang, Mengqiao Liu, et al.2026 · 8 citations
8. MAVEN-FACT: A Large-scale Event Factuality Detection DatasetFindings of the Association for Computational LinguisticsChunyang Li, Hao Peng, Xiaozhi Wang, et al.2024 · 6 citations
9. Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Yanzhi Tian, Cunxiang Wang, Zeming Liu, et al.2026 · 5 citations
10. Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and OpportunitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Changdae Oh, Seongheon Park, To Eun Kim, et al.2026 · 4 citations
11. 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
12. 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
13. 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
14. 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
15. AJ-Bench: Benchmarking Agent-as-a-Judge for Environment-Aware EvaluationFindings of the Association for Computational LinguisticsWentao Shi, Yu Wang, Yuyang Zhao, et al.2026
16. Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning ModelsFindings of the Association for Computational LinguisticsHoang Phan, Xianjun Yang, Yuanshun Yao, et al.2026
17. Complex-IF and Beyond: Expert Rubrics for RLVRWorkshop on Generation, Evaluation and Metrics (GEM)Sushant Mehta, Liudas Panavas, Eleanor Fleming, et al.2026
18. Contrastively Pre-trained Event Embeddings with Schema-free LLM AnnotationsLanguage Resources and Evaluation Conference (LREC)Frank Mtumbuka, Steven Schockaert2026
19. From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation TasksFindings of the Association for Computational LinguisticsQingyu Ren, Tianjun Pan, Xingzhou Chen, et al.2026
20. MEUR: A Benchmark for Evaluating Vision-Language Models on Multimodal Event Understanding and ReasoningLanguage Resources and Evaluation Conference (LREC)Zimu Wang, Yuqi Wang, Tong Chen, et al.2026
21. 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
22. RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsXiaobin Tian, Shuai Yuan, Muyun Ding, et al.2026
23. WildReward: Learning Reward Models from In-the-Wild Human InteractionsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.2026

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