🧑‍🔬 Who cites Qing Liu

181 citations of their works from 181 papers of our library (of the 149,439 whose bibliographies we read) · 63 with a page here, the most cited first · ← Qing Liu

1. LLaMA: Open and Efficient Foundation Language ModelsarXiv:2302.13971Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.2023 · 9,603 citations
2. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 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. Visual Instruction TuningarXiv:2304.08485Haotian Liu, Chunyuan Li, Qingyang Wu, et al.2023 · 2,617 citations
6. 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
7. 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
8. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
9. HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging FaceConference on Neural Information Processing Systems (NeurIPS)Yongliang Shen, Kaitao Song, Xu Tan, et al.2023 · 756 citations
10. CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model SocietyConference on Neural Information Processing Systems (NeurIPS)Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.2023 · 706 citations
11. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
12. Instruction Tuning with GPT-4arXiv:2304.03277Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023 · 662 citations
13. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
14. Gorilla: Large Language Model Connected with Massive APIsConference on Neural Information Processing Systems (NeurIPS)Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.2023 · 546 citations
15. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
16. Large Language Models: A SurveyarXiv:2402.06196Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.2024 · 471 citations
17. FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPUarXiv:2303.06865Ying Sheng, Lianmin Zheng, Binhang Yuan, et al.2023 · 402 citations
18. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
19. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
20. A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
21. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
22. How Far Can Camels Go? Exploring the State of Instruction Tuning on Open ResourcesConference on Neural Information Processing Systems (NeurIPS)Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.2023 · 317 citations
23. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
24. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
25. NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each BenchmarkFindings of the Association for Computational LinguisticsOscar Sainz, Jon Campos, Iker García-Ferrero, et al.2023 · 250 citations
26. A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language ModelsarXiv:2401.01313S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, et al.2024 · 249 citations
27. Specializing Smaller Language Models towards Multi-Step ReasoningarXiv:2301.12726Yao Fu, Hao Peng, Litu Ou, et al.2023 · 224 citations
28. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
29. 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
30. Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 172 citations
31. Evaluating Correctness and Faithfulness of Instruction-Following Models for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, et al.2024 · 149 citations
32. RA-DIT: Retrieval-Augmented Dual Instruction TuningarXiv:2310.01352Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.2023 · 149 citations
33. PMC-LLaMA: Towards Building Open-source Language Models for MedicinearXiv:2304.14454Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.2023 · 146 citations
34. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
35. InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 136 citations
36. Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsFindings of the Association for Computational LinguisticsKai Zhang, Bernal Jimenez Gutierrez, Yu Su2023 · 118 citations
37. The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Seungone Kim, Se Joo, Doyoung Kim, et al.2023 · 118 citations
38. SemDeDup: Data-efficient learning at web-scale through semantic deduplicationarXiv:2303.09540Amro Abbas, Kushal Tirumala, Dániel Simig, et al.2023 · 108 citations
39. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
40. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
41. On the Tool Manipulation Capability of Open-source Large Language ModelsarXiv:2305.16504Qiantong Xu, Fenglu Hong, Bo Li, et al.2023 · 92 citations
42. Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence TasksConference on Empirical Methods in Natural Language Processing (EMNLP)Andrea Sottana, Bin Liang, Kai Zou, et al.2023 · 89 citations
43. 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
44. D4: Improving LLM Pretraining via Document De-Duplication and DiversificationConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.2023 · 81 citations
45. Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive TasksConference on Neural Information Processing Systems (NeurIPS)Minki Kang, Seanie Lee, Jinheon Baek, et al.2023 · 71 citations
46. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 70 citations
47. Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic PromptingConference of the European Chapter of the Association for Computational Linguistics (EACL)Tilman Beck, Hendrik Schuff, Anne Lauscher, et al.2024 · 69 citations
48. ChatQA: Surpassing GPT-4 on Conversational QA and RAGConference on Neural Information Processing Systems (NeurIPS)Zihan Liu, Wei Ping, Rajarshi Roy, et al.2024 · 58 citations
49. DeepSeek-OCR: Contexts Optical CompressionarXiv:2510.18234Haoran Wei, Yaofeng Sun, Yukun Li2025 · 54 citations
50. Understanding Catastrophic Forgetting in Language Models via Implicit InferencearXiv:2309.10105Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan2023 · 45 citations
51. When does In-context Learning Fall Short and Why? A Study on Specification-Heavy TasksarXiv:2311.08993Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.2023 · 42 citations
52. Airavata: Introducing Hindi Instruction-tuned LLMarXiv:2401.15006Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain, et al.2024 · 31 citations
53. Investigating Hallucinations in Pruned Large Language Models for Abstractive SummarizationTransactions of the Association for Computational Linguistics (TACL)George Chrysostomou, Zhixue Zhao, Miles Williams, et al.2024 · 27 citations
54. DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AIFindings of the Association for Computational LinguisticsJianguo Zhang, Kun Qian, Zhiwei Liu, et al.2023 · 21 citations
55. Efficiently Adapting Pretrained Language Models To New LanguagesarXiv:2311.05741Zoltan Csaki, Pian Pawakapan, Urmish Thakker, et al.2023 · 21 citations
56. Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Runxuan Liu, Bei Luo, Jiaqi Li, et al.2025 · 15 citations
57. Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual ProgressarXiv:2408.14960Ayomide Odumakinde, Daniel D'souza, Pat Verga, et al.2024 · 12 citations
58. DeepSeek-OCR 2: Visual Causal FlowarXiv:2601.20552Haoran Wei, Yaofeng Sun, Yukun Li2026 · 8 citations
59. Fine-tuning Large Language Models with Limited Data: A Survey and Practical GuideTransactions of the Association for Computational Linguistics (TACL)Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.2026 · 7 citations
60. Identifying Bias in Machine-generated Text DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Kevin Stowe, Svetlana Afanaseva, Rodolfo C. Raimundo, et al.2026 · 1 citation
61. Interactive Semantic Parsing with Reinforcement Learning for Knowledge Graph ReasoningFindings of the Association for Computational LinguisticsYurun Song, Xiangqing Shen, Jianfei Yu, et al.2026
62. Reasoning with Ontology Graph: Toward Type-Constrained Knowledge Graph Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Yongxue Shan, Jie Peng, Zixuan Dong, et al.2026
63. Which bird does not have wings: Negative-constrained KGQA with Schema-guided Semantic Matching and Self-directed RefinementFindings of the Association for Computational LinguisticsMidan Shim, Seokju Hwang, KaeHyun Um, et al.2026

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