🧑‍🔬 Who cites Jing Qian

256 citations of their works from 256 papers of our library (of the 141,840 whose bibliographies we read) · 23 with a page here, the most cited first · ← Jing Qian

1. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 778 citations
2. Social Bias Frames: Reasoning about Social and Power Implications of LanguageAnnual Meeting of the Association for Computational Linguistics (ACL)Maarten Sap, Saadia Gabriel, Lianhui Qin, et al.2020 · 681 citations
3. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsarXiv:2309.12284Longhui Yu, Weisen Jiang, Han Shi, et al.2023 · 556 citations
4. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 517 citations
5. A Survey on Model Compression for Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Xunyu Zhu, Jian Li, Yong Liu, et al.2024 · 381 citations
6. Teaching Small Language Models to ReasonAnnual Meeting of the Association for Computational Linguistics (ACL)Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, et al.2023 · 340 citations
7. RLPrompt: Optimizing Discrete Text Prompts with Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.2022 · 328 citations
8. On-Policy Distillation of Language Models: Learning from Self-Generated MistakesarXiv:2306.13649Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.2023 · 288 citations
9. Measuring Faithfulness in Chain-of-Thought ReasoningarXiv:2307.13702Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.2023 · 249 citations
10. Specializing Smaller Language Models towards Multi-Step ReasoningarXiv:2301.12726Yao Fu, Hao Peng, Litu Ou, et al.2023 · 222 citations
11. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 217 citations
12. SemEval-2023 Task 10: Explainable Detection of Online SexismInternational Workshop on Semantic Evaluation (SemEval)Hannah Kirk, Wenjie Yin, Bertie Vidgen, et al.2023 · 185 citations
13. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
14. Introducing CAD: the Contextual Abuse DatasetConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bertie Vidgen, Dong Nguyen, Helen Margetts, et al.2021 · 147 citations
15. SCOTT: Self-Consistent Chain-of-Thought DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Peifeng Wang, Zhengyang Wang, Zheng Li, et al.2023 · 145 citations
16. Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-StepAnnual Meeting of the Association for Computational Linguistics (ACL)Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.2023 · 139 citations
17. A Survey on Recent Advances in LLM-Based Multi-turn Dialogue SystemsACM Computing SurveysZihao Yi, Jiarui Ouyang, Zhe Xu, et al.2024 · 129 citations
18. Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate SpeechAnnual Meeting of the Association for Computational Linguistics (ACL)Margherita Fanton, Helena Bonaldi, Serra Sinem Tekiroğlu, et al.2021 · 118 citations
19. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 113 citations
20. On Learning to Summarize with Large Language Models as ReferencesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yixin Liu, Kejian Shi, Katherine He, et al.2024 · 94 citations
21. Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought ReasoningFindings of the Association for Computational LinguisticsDebjit Paul, Robert West, Antoine Bosselut, et al.2024 · 77 citations
22. A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLIFindings of the Association for Computational LinguisticsBeiduo Chen, Siyao Peng, Anna Korhonen, et al.2025 · 9 citations
23. Explainable AI for Ethical Counter Speech Generation in Hate Speech MitigationLanguage Resources and Evaluation Conference (LREC)Ashiful Islam Ridoy, Mohammed Faisal, Yogesh Kumar, et al.2026

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