🧑‍🔬 Who cites Shengping Liu

197 citations of their works from 197 papers of our library (of the 149,439 whose bibliographies we read) · 63 with a page here, the most cited first · ← Shengping Liu

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
3. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsarXiv:2309.12284Longhui Yu, Weisen Jiang, Han Shi, et al.2023 · 565 citations
4. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingarXiv:2305.11738Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 326 citations
5. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 322 citations
6. Chain-of-Verification Reduces Hallucination in Large Language ModelsarXiv:2309.11495Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.2023 · 305 citations
7. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
8. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
9. 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
10. MiniCheck: Efficient Fact-Checking of LLMs on Grounding DocumentsConference on Empirical Methods in Natural Language Processing (EMNLP)Liyan Tang, Philippe Laban, Greg Durrett2024 · 166 citations
11. 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
12. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
13. 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
14. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
15. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
16. AlphaMath Almost Zero: Process Supervision without ProcessConference on Neural Information Processing Systems (NeurIPS)Guoxin Chen, Minpeng Liao, Chengxi Li, et al.2024 · 120 citations
17. LLM Self Defense: By Self Examination, LLMs Know They Are Being TrickedarXiv:2308.07308Mansi Phute, Alec Helbling, Matthew Hull, et al.2023 · 119 citations
18. Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-VerificationarXiv:2308.07921Aojun Zhou, Ke Wang, Zimu Lu, et al.2023 · 110 citations
19. Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?Annual Meeting of the Association for Computational Linguistics (ACL)Qineng Wang, Zihao Wang, Ying Su, et al.2024 · 107 citations
20. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
21. TrueTeacher: Learning Factual Consistency Evaluation with Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.2023 · 106 citations
22. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem ComplexityConference on Neural Information Processing Systems (NeurIPS)Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.2025 · 104 citations
23. SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step ReasoningarXiv:2308.00436Ning Miao, Yee Whye Teh, Tom Rainforth2023 · 101 citations
24. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
25. Why Do Multi-Agent LLM Systems Fail?arXiv:2503.13657Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.2025 · 89 citations
26. LLMs Can't Plan, But Can Help Planning in LLM-Modulo FrameworksarXiv:2402.01817 · Proceedings of the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, et al.2024 · 88 citations
27. Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and ObservationsFindings of the Association for Computational LinguisticsNuo Chen, Zinan Zheng, Ning Wu, et al.2024 · 86 citations
28. LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
29. OVM, Outcome-supervised Value Models for Planning in Mathematical ReasoningFindings of the Association for Computational LinguisticsFei Yu, Anningzhe Gao, Benyou Wang2023 · 78 citations
30. G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language ModelarXiv:2312.11370Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.2023 · 76 citations
31. Self-Contrast: Better Reflection Through Inconsistent Solving PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.2024 · 75 citations
32. Mutual Reasoning Makes Smaller LLMs Stronger Problem-SolversarXiv:2408.06195Zhenting Qi, Mingyuan Ma, Jiahang Xu, et al.2024 · 74 citations
33. CycleResearcher: Improving Automated Research via Automated ReviewarXiv:2411.00816Yixuan Weng, Minjun Zhu, Guangsheng Bao, et al.2024 · 65 citations
34. MARIO: MAth Reasoning with code Interpreter Output - A Reproducible PipelineFindings of the Association for Computational LinguisticsMinpeng Liao, Chengxi Li, Wei Luo, et al.2024 · 64 citations
35. Puzzle Solving using Reasoning of Large Language Models: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos, et al.2024 · 48 citations
36. NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity ClassesAnnual Meeting of the Association for Computational Linguistics (ACL)Lizhou Fan, Wenyue Hua, Lingyao Li, et al.2024 · 47 citations
37. 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
38. On Memorization of Large Language Models in Logical ReasoningInternational Joint Conference on Natural Language Processing (IJCNLP)Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.2025 · 45 citations
39. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
40. Knowledge Boundary of Large Language Models: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Moxin Li, Yong Zhao, Wenxuan Zhang, et al.2025 · 30 citations
41. Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM SamplingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guangya Wan, Yuqi Wu, Jie Chen, et al.2025 · 29 citations
42. StateFlow: Enhancing LLM Task-Solving through State-Driven WorkflowsarXiv:2403.11322Yiran Wu, Tianwei Yue, Shaokun Zhang, et al.2024 · 25 citations
43. Personality Alignment of Large Language ModelsarXiv:2408.11779Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2024 · 21 citations
44. MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought VerificationAnnual Meeting of the Association for Computational Linguistics (ACL)Linzhuang Sun, Hao Liang, Jingxuan Wei, et al.2025 · 19 citations
45. A Survey of Post-Training Scaling in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hanyu Lai, Xiao Liu, Junjie Gao, et al.2025 · 18 citations
46. ChemAgent: Self-updating Library in Large Language Models Improves Chemical ReasoningarXiv:2501.06590Xiangru Tang, Tianyu Hu, Muyang Ye, et al.2025 · 15 citations
47. Preference Optimization for Reasoning with Pseudo FeedbackarXiv:2411.16345Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.2024 · 15 citations
48. EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Yao Shi, Rongkeng Liang, Yong Xu2025 · 14 citations
49. Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes OnarXiv:2407.08348Liang Zeng, Liangjun Zhong, Liang Zhao, et al.2024 · 14 citations
50. Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsYuan Sui, Yufei He, Tri Cao, et al.2026 · 13 citations
51. CER: Confidence Enhanced Reasoning in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Ali Razghandi, Seyed Mohammad Hadi Hosseini, Mahdieh Soleymani Baghshah2025 · 8 citations
52. MetaScale: Test-Time Scaling with Evolving Meta-ThoughtsFindings of the Association for Computational LinguisticsQin Liu, Wenxuan Zhou, Nan Xu, et al.2026 · 7 citations
53. R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement LearningFindings of the Association for Computational LinguisticsQingfei Zhao, Ruobing Wang, Dingling Xu, et al.2026 · 7 citations
54. Weaver: Interweaving SQL and LLM for Table ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Rohit Khoja, Devanshu Gupta, Yanjie Fu, et al.2025 · 6 citations
55. PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question AnsweringWookje Han, Jinsol Park, Kyungjae Lee2023 · 4 citations
56. Exploring Iterative Controllable Summarization with Large Language ModelsFindings of the Association for Computational LinguisticsSangwon Ryu, Heejin Do, Daehui Kim, et al.2026 · 2 citations
57. AdapThink: Adaptive Thinking Preferences for Reasoning Language ModelsFindings of the Association for Computational LinguisticsWenyue Xu, Xu Wan, Wei Wang, et al.2026
58. CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Dingling Xu, Ruobing Wang, Qingfei Zhao, et al.2026
59. Joint Optimization of Training Data and Policy in RLHFFindings of the Association for Computational LinguisticsZhuohao Yu, Jiali Zeng, Weizheng Gu, et al.2026
60. KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsXiao Zhang, Qianru Meng, Yongjian Chen, et al.2026
61. ReActR: Reasoning through Error-Activated Reflection for LLM Post-TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Lina Sun2026
62. Taming Object Hallucinations with Verified Atomic Confidence EstimationConference of the European Chapter of the Association for Computational Linguistics (EACL)Jiarui Liu, Weihao Xuan, Zhijing Jin, et al.2026
63. ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.2026

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