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Who cites Ruiqi Zhong

1,083 citations of their works from 969 papers of our library (of the 149,439 whose bibliographies we read) · 192 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Ruiqi Zhong

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  1. LLaMA: Open and Efficient Foundation Language ModelsarXiv:2302.13971Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.2023 · 9,603 citations
  2. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language ProcessingACM Computing SurveysPengfei Liu, Weizhe Yuan, Jinlan Fu, et al.2021 · 5,423 citations
  3. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  4. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  5. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
  6. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  7. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
  8. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,556 citations
  9. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?Conference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Xinxi Lyu, Ari Holtzman, et al.2022 · 1,444 citations
  10. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
  11. 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
  12. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  13. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 831 citations
  14. Explainability for Large Language Models: A SurveyACM Transactions on Intelligent Systems and TechnologyHaiyan Zhao, Hanjie Chen, Fan Yang, et al.2023 · 790 citations
  15. Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.2022 · 754 citations
  16. SWE-bench: Can Language Models Resolve Real-World GitHub Issues?arXiv:2310.06770Carlos E. Jimenez, John Yang, Alexander Wettig, et al.2024 · 704 citations
  17. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  18. Instruction Tuning with GPT-4arXiv:2304.03277Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023 · 662 citations
  19. Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code GenerationConference on Neural Information Processing Systems (NeurIPS)Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, et al.2023 · 648 citations
  20. MetaGPT: Meta Programming for A Multi-Agent Collaborative FrameworkarXiv:2308.00352Sirui Hong, Mingchen Zhuge, Jiaqi Chen, et al.2023 · 630 citations
  21. Instruction-Following Evaluation for Large Language ModelsarXiv:2311.07911Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.2023 · 615 citations
  22. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
  23. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
  24. Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
  25. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsarXiv:2309.12284Longhui Yu, Weisen Jiang, Han Shi, et al.2023 · 565 citations
  26. SWE-agent: Agent-Computer Interfaces Enable Automated Software EngineeringConference on Neural Information Processing Systems (NeurIPS)John Yang, Carlos E. Jimenez, Alexander Wettig, et al.2024 · 552 citations
  27. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  28. PPT: Pre-trained Prompt Tuning for Few-shot LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxian Gu, Xu Han, Zhiyuan Liu, et al.2022 · 471 citations
  29. CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-XACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)Qinkai Zheng, Xiao Xia, Xu Zou, et al.2023 · 465 citations
  30. Text-to-SQL Empowered by Large Language Models: A Benchmark EvaluationProceedings of the VLDB EndowmentDawei Gao, Haibin Wang, Yaliang Li, et al.2023 · 463 citations
  31. LinkBERT: Pretraining Language Models with Document LinksAnnual Meeting of the Association for Computational Linguistics (ACL)Michihiro Yasunaga, Jure Leskovec, Percy Liang2022 · 458 citations
  32. 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
  33. UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianbao Xie, Chen Henry Wu, Peng Shi, et al.2022 · 407 citations
  34. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
  35. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  36. A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  37. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
  38. 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 · 338 citations
  39. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
  40. InternLM2 Technical ReportarXiv:2403.17297Zheng Cai, Maosong Cao, Haojiong Chen, et al.2024 · 301 citations
  41. 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
  42. RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLProceedings of the AAAI Conference on Artificial IntelligenceHaoyang Li, Jing Zhang, Cuiping Li, et al.2023 · 277 citations
  43. ZeroGen: Efficient Zero-shot Learning via Dataset GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Jiacheng Ye, Jiahui Gao, Qintong Li, et al.2022 · 245 citations
  44. 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
  45. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
  46. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
  47. Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
  48. 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
  49. Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.2024 · 206 citations
  50. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
  51. Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP ResearchersarXiv:2409.04109Chenglei Si, Diyi Yang, Tatsunori Hashimoto2024 · 196 citations
  52. One Embedder, Any Task: Instruction-Finetuned Text EmbeddingsarXiv:2212.09741Hongjin Su, Weijia Shi, Jungo Kasai, et al.2022 · 194 citations
  53. Adapting Language Models to Compress ContextsConference on Empirical Methods in Natural Language Processing (EMNLP)Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.2023 · 182 citations
  54. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  55. Large Language Models are few(1)-shot Table ReasonersFindings of the Association for Computational LinguisticsWenhu Chen2023 · 182 citations
  56. KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 178 citations
  57. Learning to Compress Prompts with Gist TokensConference on Neural Information Processing Systems (NeurIPS)Jesse Mu, Xiang Lisa Li, Noah Goodman2023 · 178 citations
  58. BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex InstructionsarXiv:2406.15877Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.2024 · 176 citations
  59. Binding Language Models in Symbolic LanguagesarXiv:2210.02875Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.2022 · 170 citations
  60. SantaCoder: don't reach for the stars!arXiv:2301.03988Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.2023 · 167 citations
  61. WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMsConference on Neural Information Processing Systems (NeurIPS)Seungju Han, Kavel Rao, Allyson Ettinger, et al.2024 · 165 citations
  62. Efficient Training of Language Models to Fill in the MiddlearXiv:2207.14255Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.2022 · 144 citations
  63. 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
  64. Diverse Demonstrations Improve In-context Compositional GeneralizationAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Levy, Ben Bogin, Jonathan Berant2023 · 141 citations
  65. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  66. A Survey on Recent Advances in LLM-Based Multi-turn Dialogue SystemsACM Computing SurveysZihao Yi, Jiarui Ouyang, Zhe Xu, et al.2024 · 130 citations
  67. Jailbreak and Guard Aligned Language Models with Only Few In-Context DemonstrationsarXiv:2310.06387Zeming Wei, Yifei Wang, Ang Li, et al.2023 · 130 citations
  68. 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
  69. A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capabilityarXiv:2303.13547Aiwei Liu, Xuming Hu, Lijie Wen, et al.2023 · 127 citations
  70. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
  71. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
  72. Deliberative Alignment: Reasoning Enables Safer Language ModelsarXiv:2412.16339Melody Y. Guan, Manas Joglekar, Eric Wallace, et al.2024 · 115 citations
  73. RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective AugmentationarXiv:2310.04408Fangyuan Xu, Weijia Shi, Eunsol Choi2023 · 115 citations
  74. Complementary Explanations for Effective In-Context LearningFindings of the Association for Computational LinguisticsXi Ye, Srinivasan Iyer, Asli Celikyilmaz, et al.2023 · 106 citations
  75. Who Wrote this Code? Watermarking for Code GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Taehyun Lee, Seokhee Hong, Jaewoo Ahn, et al.2024 · 103 citations
  76. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  77. 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
  78. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
  79. 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
  80. WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 92 citations
  81. LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language TextsAnnual Meeting of the Association for Computational Linguistics (ACL)Helia Hashemi, Jason Eisner, Corby Rosset, et al.2024 · 88 citations
  82. Rethinking Interpretability in the Era of Large Language ModelsarXiv:2402.01761Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.2024 · 87 citations
  83. Large Language Model Instruction Following: A Survey of Progresses and ChallengesComputational LinguisticsRenze Lou, Kai Zhang, Wenpeng Yin2024 · 83 citations
  84. DOC: Improving Long Story Coherence With Detailed Outline ControlAnnual Meeting of the Association for Computational Linguistics (ACL)Kevin Yang, Dan Klein, Nanyun Peng, et al.2023 · 83 citations
  85. LLMs Get Lost In Multi-Turn ConversationarXiv:2505.06120Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, et al.2025 · 82 citations
  86. OpenCoder: The Open Cookbook for Top-Tier Code Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.2025 · 81 citations
  87. 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
  88. OR-Bench: An Over-Refusal Benchmark for Large Language ModelsarXiv:2405.20947Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.2024 · 76 citations
  89. Multi-VALUE: A Framework for Cross-Dialectal English NLPCaleb Ziems, William Held, Jingfeng Yang, et al.2023 · 76 citations
  90. Benchmarking Large Language Models on Answering and Explaining Challenging Medical QuestionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanjie Chen, Zhouxiang Fang, Yash Singla, et al.2025 · 75 citations
  91. Language Models as Inductive ReasonersConference of the European Chapter of the Association for Computational Linguistics (EACL)Zonglin Yang, Li Dong, Xinya Du, et al.2024 · 70 citations
  92. 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
  93. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  94. 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
  95. OpenAgents: An Open Platform for Language Agents in the WildarXiv:2310.10634Tianbao Xie, Fan Zhou, Zhoujun Cheng, et al.2023 · 62 citations
  96. In-context Pretraining: Language Modeling Beyond Document BoundariesarXiv:2310.10638Weijia Shi, Sewon Min, Maria Lomeli, et al.2023 · 61 citations
  97. The Art of Saying No: Contextual Noncompliance in Language ModelsConference on Neural Information Processing Systems (NeurIPS)Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.2024 · 56 citations
  98. XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and RetrievalAnnual Meeting of the Association for Computational Linguistics (ACL)Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.2024 · 51 citations
  99. PanGu-Coder: Program Synthesis with Function-Level Language ModelingarXiv:2207.11280Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.2022 · 49 citations
  100. Getting the most out of your tokenizer for pre-training and domain adaptationarXiv:2402.01035Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere2024 · 47 citations

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