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Who cites Ansong Ni

551 citations of their works from 531 papers of our library (of the 149,439 whose bibliographies we read) · 111 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Ansong Ni

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  1. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  2. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  3. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  4. A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the UglyarXiv:2312.02003Yifan Yao, Jinhao Duan, Kaidi Xu, et al.2023 · 1,186 citations
  5. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
  6. Instruction Tuning with GPT-4arXiv:2304.03277Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023 · 662 citations
  7. MetaGPT: Meta Programming for A Multi-Agent Collaborative FrameworkarXiv:2308.00352Sirui Hong, Mingchen Zhuge, Jiaqi Chen, et al.2023 · 630 citations
  8. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
  9. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  10. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  11. LinkBERT: Pretraining Language Models with Document LinksAnnual Meeting of the Association for Computational Linguistics (ACL)Michihiro Yasunaga, Jure Leskovec, Percy Liang2022 · 458 citations
  12. Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLsConference on Neural Information Processing Systems (NeurIPS)Jinyang Li, Binyuan Hui, Ge Qu, et al.2023 · 433 citations
  13. Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical ReasoningarXiv:2305.12295Liangming Pan, Alon Albalak, Xinyi Wang, et al.2023 · 374 citations
  14. A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  15. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
  16. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingarXiv:2305.11738Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 326 citations
  17. AlignScore: Evaluating Factual Consistency with A Unified Alignment FunctionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuheng Zha, Yichi Yang, Ruichen Li, et al.2023 · 284 citations
  18. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsarXiv:2308.01825Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 261 citations
  19. Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-ThoughtarXiv:2210.01240Abulhair Saparov, He He2022 · 244 citations
  20. OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of GeneralizationarXiv:2212.12017Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.2022 · 244 citations
  21. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  22. Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.2024 · 207 citations
  23. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  24. Large Language Models are few(1)-shot Table ReasonersFindings of the Association for Computational LinguisticsWenhu Chen2023 · 182 citations
  25. 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
  26. LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 172 citations
  27. Generating Sequences by Learning to Self-CorrectarXiv:2211.00053Sean Welleck, Ximing Lu, Peter West, et al.2022 · 172 citations
  28. Binding Language Models in Symbolic LanguagesarXiv:2210.02875Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.2022 · 170 citations
  29. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 161 citations
  30. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 159 citations
  31. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 147 citations
  32. In-Context Learning for Few-Shot Dialogue State TrackingFindings of the Association for Computational LinguisticsYushi Hu, Chia-Hsuan Lee, Tianbao Xie, et al.2022 · 144 citations
  33. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
  34. Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and BeyondIEEE Transactions on Knowledge and Data EngineeringFangzhi Xu, Qika Lin, Jiawei Han, et al.2023 · 142 citations
  35. Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  36. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  37. Faithful Logical Reasoning via Symbolic Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Liangming Pan, et al.2024 · 129 citations
  38. MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual DataAnnual Meeting of the Association for Computational Linguistics (ACL)Yilun Zhao, Yunxiang Li, Chenying Li, et al.2022 · 128 citations
  39. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
  40. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
  41. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  42. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  43. InterCode: Standardizing and Benchmarking Interactive Coding with Execution FeedbackConference on Neural Information Processing Systems (NeurIPS)John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.2023 · 95 citations
  44. LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.2024 · 93 citations
  45. Universal Self-Consistency for Large Language Model GenerationarXiv:2311.17311Xinyun Chen, Renat Aksitov, Uri Alon, et al.2023 · 92 citations
  46. LAMBADA: Backward Chaining for Automated Reasoning in Natural LanguageAnnual Meeting of the Association for Computational Linguistics (ACL)Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.2023 · 89 citations
  47. Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD ExamplesConference on Neural Information Processing Systems (NeurIPS)Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.2023 · 84 citations
  48. KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge GraphAnnual Meeting of the Association for Computational Linguistics (ACL)Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, et al.2025 · 78 citations
  49. Multi-VALUE: A Framework for Cross-Dialectal English NLPCaleb Ziems, William Held, Jingfeng Yang, et al.2023 · 76 citations
  50. ReCEval: Evaluating Reasoning Chains via Correctness and InformativenessConference on Empirical Methods in Natural Language Processing (EMNLP)Archiki Prasad, Swarnadeep Saha, Xiang Zhou, et al.2023 · 73 citations
  51. MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQLInternational Conference on Computational Linguistics (COLING)Bing Wang, Changyu Ren, Jian Yang, et al.2025 · 68 citations
  52. Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
  53. OpenAgents: An Open Platform for Language Agents in the WildarXiv:2310.10634Tianbao Xie, Fan Zhou, Zhoujun Cheng, et al.2023 · 62 citations
  54. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  55. MathChat: Converse to Tackle Challenging Math Problems with LLM AgentsarXiv:2306.01337Yiran Wu; Feiran Jia; Shaokun Zhang; Hangyu Li; Erkang Zhu; Yue Wang; Yin Tat Lee; Richard Peng; Qingyun Wu;, Chi Wang2023 · 46 citations
  56. Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Nisarg Patel, Mohith Kulkarni, Mihir Parmar, et al.2024 · 39 citations
  57. Through the Lens of Core Competency: Survey on Evaluation of Large Language ModelsarXiv:2308.07902Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.2023 · 35 citations
  58. mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Huiyuan Lai, Malvina Nissim2024 · 34 citations
  59. Augmented Large Language Models with Parametric Knowledge GuidingarXiv:2305.04757Ziyang Luo, Can Xu, Pu Zhao, et al.2023 · 32 citations
  60. When is Tree Search Useful for LLM Planning? It Depends on the DiscriminatorAnnual Meeting of the Association for Computational Linguistics (ACL)Ziru Chen, Michael White, Ray Mooney, et al.2024 · 28 citations
  61. L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.2024 · 27 citations
  62. Logical Reasoning over Natural Language as Knowledge Representation: A SurveyarXiv:2303.12023Zonglin Yang, Xinya Du, Rui Mao, et al.2023 · 27 citations
  63. Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language ModelsarXiv:2310.00836Man Luo, Shrinidhi Kumbhar, Ming shen, et al.2023 · 27 citations
  64. S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruotian Ma, Peisong Wang, Cheng Liu, et al.2025 · 26 citations
  65. How Likely Do LLMs with CoT Mimic Human Reasoning?International Conference on Computational Linguistics (COLING)Guangsheng Bao, Hongbo Zhang, Cunxiang Wang, et al.2025 · 22 citations
  66. A Survey on Evaluation of LLM-based AgentsFindings of the Association for Computational LinguisticsAsaf Yehudai, Lilach Eden, Alan Li, et al.2026 · 21 citations
  67. CodeI/O: Condensing Reasoning Patterns via Code Input-Output PredictionarXiv:2502.07316Junlong Li, Daya Guo, Dejian Yang, et al.2025 · 21 citations
  68. CodeTree: Agent-guided Tree Search for Code Generation with Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jierui Li, Hung Le, Yingbo Zhou, et al.2025 · 21 citations
  69. RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World ScenariosAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiwen Zhou, Wenyue Hua, Liangming Pan, et al.2025 · 21 citations
  70. StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement LearningACM International Conference on Information and Knowledge Management (CIKM)Yuanqing Yu, Zhefan Wang, Weizhi Ma, et al.2024 · 20 citations
  71. Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Dayu Yang, Tianyang Liu, Daoan Zhang, et al.2025 · 19 citations
  72. ALGO: Synthesizing Algorithmic Programs with LLM-Generated Oracle VerifiersarXiv:2305.14591Kexun Zhang, Danqing Wang, Jingtao Xia, et al.2023 · 19 citations
  73. RECKONING: Reasoning through Dynamic Knowledge EncodingConference on Neural Information Processing Systems (NeurIPS)Zeming Chen, Gail Weiss, Eric Mitchell, et al.2023 · 19 citations
  74. Logical Phase Transitions: Understanding Collapse in LLM Logical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Xinglang Zhang, Yunyao Zhang, ZeLiang Chen, et al.2026 · 17 citations
  75. STaR-SQL: Self-Taught Reasoner for Text-to-SQLAnnual Meeting of the Association for Computational Linguistics (ACL)Mingqian He, Yongliang Shen, Wenqi Zhang, et al.2025 · 17 citations
  76. Skills-in-Context Prompting: Unlocking Compositionality in Large Language ModelsarXiv:2308.00304Jiaao Chen, Xiaoman Pan, Dian Yu, et al.2023 · 17 citations
  77. Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Meng Luo, et al.2025 · 16 citations
  78. Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.2025 · 15 citations
  79. From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical DebuggingarXiv:2410.01215Yuling Shi, Songsong Wang, Chengcheng Wan, et al.2024 · 15 citations
  80. Semantic-Aware Logical Reasoning via a Semiotic FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Yunyao Zhang, Xinglang Zhang, Junxi Sheng, et al.2026 · 13 citations
  81. JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language ModelsarXiv:2501.14851Michael K. Chen, Xikun Zhang, Dacheng Tao2025 · 10 citations
  82. MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyuan Li, Keqin Bao, Yubo Ma, et al.2026 · 9 citations
  83. RGR-KBQA: Generating Logical Forms for Question Answering Using Knowledge-Graph-Enhanced Large Language ModelInternational Conference on Computational Linguistics (COLING)Tengfei Feng, Liang He2025 · 9 citations
  84. EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence CheckingConference on Empirical Methods in Natural Language Processing (EMNLP)Anjiang Wei, Jiannan Cao, Ran Li, et al.2025 · 8 citations
  85. LogicPro: Improving Complex Logical Reasoning via Program-Guided LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Jiang, Yuchen Yan, Yang Liu, et al.2025 · 8 citations
  86. Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical ProblemsProceedings of the AAAI Conference on Artificial IntelligenceJunyi Ye, Jingyi Gu, Xinyun Zhao, et al.2024 · 8 citations
  87. Deliberate Reasoning in Language Models as Structure-Aware Planning with an Accurate World ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Siheng Xiong, Ali Payani, Yuan Yang, et al.2025 · 7 citations
  88. InductionBench: LLMs Fail in the Simplest Complexity ClassAnnual Meeting of the Association for Computational Linguistics (ACL)Wenyue Hua, Tyler Wong, Fei Sun, et al.2025 · 5 citations
  89. 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
  90. J4R: Learning to Judge with Equivalent Initial State Group Relative Policy OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.2026 · 3 citations
  91. NL2Logic: AST-Guided Translation of Natural Language into First-Order Logic with Large Language ModelsFindings of the Association for Computational LinguisticsRizky Ramadhana Putra, Raihan Sultan Pasha Basuki, Yutong Cheng, et al.2026 · 3 citations
  92. ToolGate: Contract-Grounded and Verified Tool Execution for LLMsFindings of the Association for Computational LinguisticsYanming Liu, Xinyue Peng, Jiannan Cao, et al.2026 · 3 citations
  93. Adaptive LLM-Symbolic Reasoning via Dynamic Logical Solver CompositionConference of the European Chapter of the Association for Computational Linguistics (EACL)Lei Xu, Pierre Beckmann, Marco Valentino, et al.2026 · 2 citations
  94. Argument-Based Consistency in Toxicity Explanations of LLMsFindings of the Association for Computational LinguisticsRamaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.2026 · 2 citations
  95. Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.2026 · 2 citations
  96. Constructing coherent spatial memory in LLM agents through graph rectificationAnnual Meeting of the Association for Computational Linguistics (ACL)Puzhen Zhang, Xuyang Chen, Yu Feng, et al.2026 · 1 citation
  97. ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Lingxiao Tang, He Ye, Zhaoyang Chu, et al.2026 · 1 citation
  98. GIL-Zaragoza at SemEval 2026 Task 11: Comparing Classification, Autoformalization, and Ontologies for Formal Reasoning CapabilitiesInternational Workshop on Semantic Evaluation (SemEval)Francisco Lopez-Ponce, Lucia Pitarch, Iván Saavedra Martínez, et al.2026 · 1 citation
  99. PV-SQL: Synergizing Database Probing and Rule-based Verification for Text-to-SQL AgentsFindings of the Association for Computational LinguisticsYuan Tian, Tianyi Zhang2026 · 1 citation
  100. ReportLogic: Evaluating Logical Quality in Deep Research ReportsAnnual Meeting of the Association for Computational Linguistics (ACL)Jujia Zhao, Zhaoxin Huan, Zihan Wang, et al.2026 · 1 citation

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