---
title: "Who cites Jingyuan Ma — 734 papers of our library"
description: "734 papers of the Elamur Research library cite the works of Jingyuan Ma, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Jingyuan Ma

734 citations of their works from 734 papers of our library (of the 149,439 whose bibliographies we read) · 125 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Jingyuan Ma](https://md.research.elamur.ai/free/en/authors/jingyuan-ma/)

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1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
3. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
4. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
5. **[In-Context Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/ram-2023-context-retrieval-augmented-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ori Ram, Yoav Levine, Itay Dalmedigos, et al.*2023 · 793 citations*
6. **[Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Zhu, Hongyi Liu, Qingxiu Dong, et al.*2024 · 506 citations*
7. **[Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/) [Proceedings of the VLDB Endowment](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-vldb-endowment/)**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 463 citations*
8. **[A Survey on Model Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations*
9. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
10. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
11. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 339 citations*
12. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
13. [**Large Language Model based Multi-Agents: A Survey of Progress and Challenges arXiv:2402.01680**Taicheng Guo, Xiuying Chen, Yaqi Wang, et al.*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-large-language-model-based/)
14. **[Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers](https://md.research.elamur.ai/free/en/papers/dai-2023-why-can-gpt-learn-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Damai Dai, Yutao Sun, Li Dong, et al.*2023 · 257 citations*
15. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
16. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
17. [**PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization arXiv:2306.05087**Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pandalm-automatic-evaluation-benchmark-llm/)
18. **[WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/he-2024-webvoyager-building-end-end-web/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2024 · 191 citations*
19. **[Towards Making the Most of ChatGPT for Machine Translation](https://md.research.elamur.ai/free/en/papers/peng-2023-making-most-chatgpt-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Keqin Peng, Liang Ding, Qihuang Zhong, et al.*2023 · 190 citations*
20. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
21. [**RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models arXiv:2310.00746**Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.*2023 · 187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
22. [**Adaptive Machine Translation with Large Language Models arXiv:2301.13294**Yasmin Moslem, Rejwanul Haque, John D. Kelleher, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/moslem-2023-adaptive-machine-translation-large-language/)
23. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
24. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
25. [**GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher arXiv:2308.06463**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-gpt-4-too-smart-safe/)
26. **[LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression](https://md.research.elamur.ai/free/en/papers/pan-2024-llmlingua-2-data-distillation-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.*2024 · 161 citations*
27. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
28. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression arXiv:2310.06839**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
29. **[Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning](https://md.research.elamur.ai/free/en/papers/wang-2023-label-words-anchors-information-flow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lean Wang, Lei Li, Damai Dai, et al.*2023 · 153 citations*
30. **[Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-really-good/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Fangzhi Xu, Qika Lin, Jiawei Han, et al.*2023 · 142 citations*
31. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
32. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/)
33. [**Large Language Models Understand and Can be Enhanced by Emotional Stimuli arXiv:2307.11760**Cheng Li, Jindong Wang, Yixuan Zhang, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-understand-enhanced/)
34. **[CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluation](https://md.research.elamur.ai/free/en/papers/tu-2024-charactereval-chinese-benchmark-role-playing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Quan Tu, Shilong Fan, Zihang Tian, et al.*2024 · 108 citations*
35. [**RestGPT: Connecting Large Language Models with Real-World RESTful APIs arXiv:2306.06624**Yifan Song, Weimin Xiong, Dawei Zhu, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/song-2023-restgpt-connecting-large-language-models/)
36. [**MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning arXiv:2310.03731**Ke Wang, Houxing Ren, Aojun Zhou, et al.*2023 · 99 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mathcoder-seamless-code-integration-llms/)
37. **[Boosting Language Models Reasoning with Chain-of-Knowledge Prompting](https://md.research.elamur.ai/free/en/papers/wang-2024-boosting-language-models-reasoning-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianing Wang, Qiushi Sun, Xiang Li, et al.*2024 · 94 citations*
38. **[Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs](https://md.research.elamur.ai/free/en/papers/jin-2024-graph-chain-thought-augmenting-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bowen Jin, Chulin Xie, Jiawei Zhang, et al.*2024 · 89 citations*
39. [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge arXiv:2311.05112**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/)
40. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations*
41. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
42. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
43. **[CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models](https://md.research.elamur.ai/free/en/papers/qian-2023-creator-tool-creation-disentangling-abstract/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Qian, Chi Han, Yi Fung, et al.*2023 · 75 citations*
44. **[Calibrating LLM-Based Evaluator](https://md.research.elamur.ai/free/en/papers/liu-2024-calibrating-llm-based-evaluator/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuxuan Liu, Tianchi Yang, Shaohan Huang, et al.*2024 · 71 citations*
45. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/)
46. **[CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information Needs in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-clamber-benchmark-identifying-clarifying-ambiguous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tong Zhang, Peixin Qin, Yang Deng, et al.*2024 · 52 citations*
47. **[ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information Extraction](https://md.research.elamur.ai/free/en/papers/he-2023-icl-d3ie-context-learning-diverse/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Jiabang He; Lei Wang; Yi Hu; Ning Liu; Hui Liu; Xing Xu;, Heng Tao Shen*2023 · 51 citations*
48. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
49. **[Puzzle Solving using Reasoning of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/giadikiaroglou-2024-puzzle-solving-reasoning-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos, et al.*2024 · 48 citations*
50. **[Improving Chain-of-Thought Reasoning via Quasi-Symbolic Abstractions](https://md.research.elamur.ai/free/en/papers/ranaldi-2025-improving-chain-thought-reasoning-quasi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Marco Valentino, Andre Freitas*2025 · 42 citations*
51. [**When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks arXiv:2311.08993**Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-context-learning-fall-short-why/)
52. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kiran Ramnath, Kang Zhou, Sheng Guan, et al.*2025 · 40 citations*
53. **[Unveiling Linguistic Regions in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-unveiling-linguistic-regions-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihao Zhang, Jun Zhao, Qi Zhang, et al.*2024 · 39 citations*
54. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
55. [**M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models arXiv:2305.10263**Chuang Liu, Renren Jin, Yuqi Ren, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-m3ke-massive-multi-level/)
56. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
57. **[Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification](https://md.research.elamur.ai/free/en/papers/zhang-2025-breaking-agents-compromising-autonomous-llm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Boyang Zhang, Yicong Tan, Yun Shen, et al.*2025 · 29 citations*
58. [**Reviewer2: Optimizing Review Generation Through Prompt Generation arXiv:2402.10886**Zhaolin Gao, Kiante Brantley, Thorsten Joachims*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-reviewer2-optimizing-review-generation-through/)
59. **[Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance](https://md.research.elamur.ai/free/en/papers/pecher-2025-comparing-specialised-small-general-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Branislav Pecher, Ivan Srba, Maria Bielikova*2025 · 24 citations*
60. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
61. **[TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence Configuration](https://md.research.elamur.ai/free/en/papers/li-2025-taco-enhancing-multimodal-context-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanshu Li, Jianjiang Yang, Tian Yun, et al.*2025 · 22 citations*
62. **[RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/zhou-2025-rulearena-benchmark-rule-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiwen Zhou, Wenyue Hua, Liangming Pan, et al.*2025 · 21 citations*
63. **[CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation](https://md.research.elamur.ai/free/en/papers/ziegler-2025-craft-your-dataset-task-specific/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.*2025 · 20 citations*
64. **[Conformity in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2025-conformity-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaochen Zhu, Caiqi Zhang, Tom Stafford, et al.*2025 · 18 citations*
65. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
66. **[Automatic Combination of Sample Selection Strategies for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/pecher-2026-automatic-combination-sample-selection-strategies/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Branislav Pecher, Ivan Srba, Maria Bielikova, et al.*2026 · 15 citations*
67. **[Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-attention-entropy-is-key-factor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhisong Zhang, Yan Wang, Xinting Huang, et al.*2025 · 14 citations*
68. **[Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhong-2025-mix-granularity-optimize-chunking-granularity/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zijie Zhong, Hanwen Liu, Xiaoya Cui, et al.*2025 · 13 citations*
69. **[UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision](https://md.research.elamur.ai/free/en/papers/fang-2026-unicorn-self-improving-unified-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Fang, Ruiyan Han, XinYu Sun, et al.*2026 · 11 citations*
70. **[Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-confidence-v-s-critique-decomposition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhe Yang, Yichang Zhang, Yudong Wang, et al.*2025 · 11 citations*
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75. [**JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models arXiv:2501.14851**Michael K. Chen, Xikun Zhang, Dacheng Tao*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-justlogic-comprehensive-benchmark-evaluating-deductive/)
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77. **[AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment](https://md.research.elamur.ai/free/en/papers/lai-2025-adacqr-enhancing-query-reformulation-conversational/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yilong Lai, Jialong Wu, Congzhi Zhang, et al.*2025 · 9 citations*
78. **[Position: LLMs Can be Good Tutors in English Education](https://md.research.elamur.ai/free/en/papers/ye-2025-position-llms-can-be-good/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jingheng Ye, Shen Wang, Deqing Zou, et al.*2025 · 9 citations*
79. **[Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs](https://md.research.elamur.ai/free/en/papers/li-2025-self-instructed-derived-prompt-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuo Li, Yuhao Du, Jinpeng Hu, et al.*2025 · 9 citations*
80. **[Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning](https://md.research.elamur.ai/free/en/papers/bi-2025-enhancing-reasoning-capabilities-small-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jing Bi, Yuting Wu, Weiwei Xing, et al.*2025 · 8 citations*
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82. **[Unveiling Language Competence Neurons: A Psycholinguistic Approach to Model Interpretability](https://md.research.elamur.ai/free/en/papers/duan-2025-unveiling-language-competence-neurons-psycholinguistic/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Xufeng Duan, Xinyu Zhou, Bei Xiao, et al.*2025 · 8 citations*
83. **[ArabicSense: A Benchmark for Evaluating Commonsense Reasoning in Arabic with Large Language Models](https://md.research.elamur.ai/free/en/papers/lamsiyah-2025-arabicsense-benchmark-evaluating-commonsense-reasoning/) [Workshop on Arabic Corpus Linguistics](https://md.research.elamur.ai/free/en/venues/wacl/)**Salima Lamsiyah, Kamyar Zeinalipour, Samir El amrany, et al.*2025 · 7 citations*
84. **[Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic](https://md.research.elamur.ai/free/en/papers/weir-2024-enhancing-systematic-decompositional-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nathaniel Weir, Kate Sanders, Orion Weller, et al.*2024 · 7 citations*
85. **[Subjectivity Detection in English News using Large Language Models](https://md.research.elamur.ai/free/en/papers/shokri-2024-subjectivity-detection-english-news-large/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Mohammad Shokri, Vivek Sharma, Elena Filatova, et al.*2024 · 7 citations*
86. **[MAVEN-FACT: A Large-scale Event Factuality Detection Dataset](https://md.research.elamur.ai/free/en/papers/li-2024-maven-fact-large-scale-event/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunyang Li, Hao Peng, Xiaozhi Wang, et al.*2024 · 6 citations*
87. [**Responsible AI for Test Equity and Quality: The Duolingo English Test as a Case Study arXiv:2409.07476**Jill Burstein, Geoffrey T. LaFlair, Kevin Yancey, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/burstein-2024-responsible-ai-test-equity-quality/)
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89. **[AudioJudge: Understanding What Works in Large Audio Model Based Speech Evaluation](https://md.research.elamur.ai/free/en/papers/manakul-2026-audiojudge-understanding-what-works-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Potsawee Manakul, Woody Haosheng Gan, Michael J Ryan, et al.*2026 · 3 citations*
90. **[How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics](https://md.research.elamur.ai/free/en/papers/cosma-2024-how-hard-is-this-test/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Adrian Cosma, Stefan Ruseti, Mihai Dascalu, et al.*2024 · 3 citations*
91. **[Beyond Many-Shot Translation: Scaling In-Context Demonstrations For Low-Resource Machine Translation](https://md.research.elamur.ai/free/en/papers/salim-2026-beyond-many-shot-translation-scaling/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Luis Frentzen Salim, Esteban Carlin, Alexandre Morinvil, et al.*2026 · 2 citations*
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93. **[Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption](https://md.research.elamur.ai/free/en/papers/liu-2026-position-llm-watermarking-should-align/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yepeng Liu, Xuandong Zhao, Dawn Song, et al.*2026 · 2 citations*
94. [**Deciphering Emotions in Children Storybooks: A Comparative Analysis of Multimodal LLMs in Educational Applications arXiv:2506.18201**Bushra Asseri, Estabraq Abdelaziz, Maha Al Mogren, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/asseri-2025-deciphering-emotions-children-storybooks-comparative/)
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96. **[Chain-of-Thought as a Lens: Evaluating Structured Reasoning Alignment between Human Preferences and Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-chain-thought-as-lens-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boxuan Wang, Zhuoyun Li, Xinmiao Huang, et al.*2026 · 1 citation*
97. **[Enhanced Reasoning for Biomedical Document-Level Relation Extraction via a Novel Cascade Language Model Framework](https://md.research.elamur.ai/free/en/papers/song-2026-enhanced-reasoning-biomedical-document-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haohua Song, Wenhao Gu, Zhijing Li, et al.*2026 · 1 citation*
98. **[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://md.research.elamur.ai/free/en/papers/ostermann-2026-weights-activations-is-steering-next/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, et al.*2026 · 1 citation*
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100. **[SSA: Improving Performance With a Better Scoring Function](https://md.research.elamur.ai/free/en/papers/naim-2026-ssa-improving-performance-better-scoring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Omar Naim, Swarnadeep Bhar, Jerome Bolte, et al.*2026 · 1 citation*

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