---
title: "Who cites Yi Chang — 899 papers of our library"
description: "899 papers of the Elamur Research library cite the works of Yi Chang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yi-chang/cited-by/"
---
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# Who cites Yi Chang

902 citations of their works from 899 papers of our library (of the 141,840 whose bibliographies we read) · 63 with a page here, the most cited first · [← Yi Chang](https://md.research.elamur.ai/free/en/authors/yi-chang/)

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 · 2,863 citations*
2. [**A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly arXiv:2312.02003**Yifan Yao, Jinhao Duan, Kaidi Xu, et al.*2023 · 1,182 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-survey-large-language-model-llm/)
3. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,074 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 · 966 citations*
5. [**Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization arXiv:2309.07430 · Nature Medicine, 2024**Dave Van Veen, Cara Van Uden, Louis Blankemeier, et al.*2023 · 928 citations*](https://md.research.elamur.ai/free/en/papers/veen-2023-adapted-large-language-models-outperform/)
6. **[MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 731 citations*
7. **[Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach](https://md.research.elamur.ai/free/en/papers/yin-2019-benchmarking-zero-shot-text-classification/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenpeng Yin, Jamaal Hay, Dan Roth*2019 · 731 citations*
8. **[Benchmarking Large Language Models in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/chen-2023-benchmarking-large-language-models-retrieval/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jiawei Chen, Hongyu Lin, Xianpei Han, et al.*2023 · 625 citations*
9. [**Instruction-Following Evaluation for Large Language Models arXiv:2311.07911**Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.*2023 · 586 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/)
10. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
11. **[TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking](https://md.research.elamur.ai/free/en/papers/wang-2020-tplinker-single-stage-joint-extraction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yucheng Wang, Bowen Yu, Yueyang Zhang, et al.*2020 · 529 citations*
12. [**Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations arXiv:2312.06674**Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/inan-2023-llama-guard-llm-based-input/)
13. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
14. **[Joint Slot Filling and Intent Detection via Capsule Neural Networks](https://md.research.elamur.ai/free/en/papers/zhang-2019-joint-slot-filling-intent-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenwei Zhang, Yaliang Li, Nan Du, et al.*2019 · 315 citations*
15. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
16. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 279 citations*
17. [**ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT arXiv:2302.10205**Xiang Wei; Xingyu Cui; Ning Cheng; Xiaobin Wang; Xin Zhang; Shen Huang; Pengjun Xie; Jinan Xu; Yufeng Chen; Meishan Zhang; Yong Jiang;, Wenjuan Han*2023 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-chatie-zero-shot-information-extraction/)
18. [**Prometheus: Inducing Fine-grained Evaluation Capability in Language Models arXiv:2310.08491**Seungone Kim, Jamin Shin, Yejin Cho, et al.*2023 · 267 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-prometheus-inducing-fine-grained-evaluation/)
19. **[Induction Networks for Few-Shot Text Classification](https://md.research.elamur.ai/free/en/papers/geng-2019-induction-networks-few-shot-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruiying Geng, Binhua Li, Yongbin Li, et al.*2019 · 263 citations*
20. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*
21. [**LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset arXiv:2309.11998**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 236 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lmsys-chat-1m-large-scale/)
22. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
23. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/)
24. [**PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization arXiv:2306.05087**Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al.*2023 · 192 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pandalm-automatic-evaluation-benchmark-llm/)
25. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
26. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
27. [**Multilingual Jailbreak Challenges in Large Language Models arXiv:2310.06474**Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-multilingual-jailbreak-challenges-large-language/)
28. [**Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers arXiv:2409.04109**Chenglei Si, Diyi Yang, Tatsunori Hashimoto*2024 · 182 citations*](https://md.research.elamur.ai/free/en/papers/si-2024-llms-generate-novel-research/)
29. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
30. **[Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 177 citations*
31. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 173 citations*
32. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
33. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning arXiv:2308.12032**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
34. [**Agent Laboratory: Using LLM Agents as Research Assistants arXiv:2501.04227**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
35. **[Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*
36. [**Time Travel in LLMs: Tracing Data Contamination in Large Language Models arXiv:2308.08493**Shahriar Golchin, Mihai Surdeanu*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/golchin-2023-time-travel-llms-tracing-data/)
37. [**Evaluating the Performance of Large Language Models on GAOKAO Benchmark arXiv:2305.12474**Xiaotian Zhang, Chunyang Li, Yi Zong, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-evaluating-performance-large-language/)
38. **[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*
39. [**Rethinking Benchmark and Contamination for Language Models with Rephrased Samples arXiv:2311.04850**Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-rethinking-benchmark-contamination-language-models/)
40. **[Data Interpreter: An LLM Agent for Data Science](https://md.research.elamur.ai/free/en/papers/hong-2025-data-interpreter-llm-agent-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sirui Hong, Yizhang Lin, Bang Liu, et al.*2025 · 89 citations*
41. **[FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-followbench-multi-level-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.*2024 · 85 citations*
42. **[SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2024-seaeval-multilingual-foundation-models-cross/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Zhengyuan Liu, Xin Huang, et al.*2024 · 85 citations*
43. [**Wider and Deeper LLM Networks are Fairer LLM Evaluators arXiv:2308.01862**Xinghua Zhang, Bowen Yu, Haiyang Yu, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-wider-deeper-llm-networks-fairer/)
44. [**AlignBench: Benchmarking Chinese Alignment of Large Language Models arXiv:2311.18743**Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.*2023 · 73 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-alignbench-benchmarking-chinese-alignment/)
45. [**Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation? arXiv:2309.07462**Rishav Hada, Varun Gumma, Adrian de Wynter, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/hada-2023-large-language-model-based-evaluators/)
46. [**CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation arXiv:2311.18702**Pei Ke, Bosi Wen, Zhuoer Feng, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/ke-2023-critiquellm-informative-critique-generation/)
47. **[Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/ma-2025-pragmatics-era-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bolei Ma, Yuting Li, Wei Zhou, et al.*2025 · 49 citations*
48. **[M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/feng-2025-m-mad-multidimensional-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaopeng Feng, Jiayuan Su, Jiamei Zheng, et al.*2025 · 24 citations*
49. **[A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection](https://md.research.elamur.ai/free/en/papers/wu-2021-context-aware-hierarchical-bert-fusion/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Ting-Wei Wu, Ruolin Su, Biing-Hwang Juang*2021 · 19 citations*
50. [**Do Large Language Models Understand Word Senses?**Domenico Meconi, Simone Stirpe, Federico Martelli*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/meconi-2025-llms-word-senses/)
51. [**MultiPragEval: Multilingual Pragmatic Evaluation of Large Language Models Proceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLP**Dojun Park, Jiwoo Lee, Seohyun Park, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/park-2024-multiprageval-multilingual-pragmatic-evaluation-large/)
52. [**Lost in Translationese? Reducing Translation Effect Using Abstract Meaning Representation**Shira Wein, Nathan Schneider*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wein-2024-lost-translationese-reducing-translation-effect/)
53. **[Pragmatic Competence Evaluation of Large Language Models for the Korean Language](https://md.research.elamur.ai/free/en/papers/park-2024-pragmatic-competence-evaluation-large-language/) [Pacific Asia Conference on Language, Information and Computation (PACLIC)](https://md.research.elamur.ai/free/en/venues/paclic/)**Dojun Park, Jiwoo Lee, Hyeyun Jeong, et al.*2024 · 11 citations*
54. [**Survey of Abstract Meaning Representation: Then, Now, Future**Behrooz Mansouri*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mansouri-2025-survey-abstract-meaning-representation-then/)
55. [**Cutting Through the Noise: Boosting LLM Performance on Math Word Problems**Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/anantheswaran-2024-cutting-through-noise-boosting-llm/)
56. **[Multilingual coreference resolution as text generation](https://md.research.elamur.ai/free/en/papers/skachkova-2024-multilingual-coreference-resolution-as-text/) [Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)](https://md.research.elamur.ai/free/en/venues/crac/)**Natalia Skachkova*2024 · 6 citations*
57. **[Advancing Arabic Sentiment Analysis: ArSen Benchmark and the Improved Fuzzy Deep Hybrid Network](https://md.research.elamur.ai/free/en/papers/fang-2024-advancing-arabic-sentiment-analysis-arsen/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Yang Fang, Cheng Xu, Shuhao Guan, et al.*2024 · 4 citations*
58. [**Evaluating large language models for the tasks of PoS tagging within the Universal Dependency framework**Mateus Machado, Evandro Ruiz*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/machado-2024-evaluating-large-language-models-tasks/)
59. **[Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026*
60. [**EDRAC: Benchmarking Arabic Dialect Reading Comprehension arXiv:2609.01113**Noor Abo Mokh, Kirill Chirkunov, Teresa Lynn, et al.*2026*](https://md.research.elamur.ai/free/en/papers/mokh-2026-edrac-benchmarking-arabic-dialect-reading/)
61. **[EL-MIA: Quantifying Membership Inference Risks of Sensitive Entities in LLMs](https://md.research.elamur.ai/free/en/papers/satvaty-2026-el-mia-quantifying-membership-inference/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ali Satvaty, Suzan Verberne, Fatih Turkmen*2026*
62. **[Evaluating LLM Style Transfer Through Readability-Based Age Assessments](https://md.research.elamur.ai/free/en/papers/maro-2026-evaluating-llm-style-transfer-through/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Maria Di Maro, Antonio Origlia, Leonilda Bilo, et al.*2026*
63. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*

836 more citing papers of our library have no page here yet.

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