🧑‍🔬 Who cites Chang Liu

246 citations of their works from 246 papers of our library (of the 149,439 whose bibliographies we read) · 59 with a page here, the most cited first · ← Chang Liu

1. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
2. RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language ModelsFindings of the Association for Computational LinguisticsSamuel Gehman, Suchin Gururangan, Maarten Sap, et al.2020 · 1,306 citations
3. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
4. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
5. Extracting Training Data from Large Language ModelsarXiv:2012.07805Nicholas Carlini, Florian Tramer, Eric Wallace, et al.2020 · 955 citations
6. Red Teaming Language Models with Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Saffron Huang, Francis Song, et al.2022 · 700 citations
7. Ethical and social risks of harm from Language ModelsarXiv:2112.04359Laura Weidinger, John Mellor, Maribeth Rauh, et al.2021 · 456 citations
8. Large Language Models Struggle to Learn Long-Tail KnowledgearXiv:2211.08411Nikhil Kandpal, Haikang Deng, Adam Roberts, et al.2022 · 366 citations
9. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
10. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
11. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT ModelsConference on Neural Information Processing Systems (NeurIPS)Boxin Wang, Weixin Chen, Hengzhi Pei, et al.2023 · 259 citations
12. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
13. Scalable Extraction of Training Data from (Production) Language ModelsarXiv:2311.17035Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.2023 · 211 citations
14. Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.2022 · 190 citations
15. Deduplicating Training Data Mitigates Privacy Risks in Language ModelsarXiv:2202.06539Nikhil Kandpal, Eric Wallace, Colin Raffel2022 · 172 citations
16. Impact of Pretraining Term Frequencies on Few-Shot Numerical ReasoningFindings of the Association for Computational LinguisticsYasaman Razeghi, Robert L Logan IV, Matt Gardner, et al.2022 · 165 citations
17. The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual DatasetarXiv:2303.03915Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.2023 · 150 citations
18. Quantifying Privacy Risks of Masked Language Models Using Membership Inference AttacksConference on Empirical Methods in Natural Language Processing (EMNLP)Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, et al.2022 · 146 citations
19. RAFT: Adapting Language Model to Domain Specific RAGarXiv:2403.10131Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.2024 · 137 citations
20. How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVENTransactions of the Association for Computational Linguistics (TACL)R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.2023 · 117 citations
21. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
22. Do Membership Inference Attacks Work on Large Language Models?arXiv:2402.07841Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.2024 · 87 citations
23. Machine Unlearning of Pre-trained Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Yao, Eli Chien, Minxin Du, et al.2024 · 86 citations
24. MoBA: Mixture of Block Attention for Long-Context LLMsConference on Neural Information Processing Systems (NeurIPS)Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.2025 · 80 citations
25. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
26. Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of PrivacyInternational Natural Language Generation Conference (INLG)Daphne Ippolito, Florian Tramer, Milad Nasr, et al.2023 · 68 citations
27. MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning AttentionarXiv:2506.13585MiniMax, Aili Chen, Aonian Li, et al.2025 · 66 citations
28. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
29. Understanding Transformer Memorization Recall Through IdiomsConference of the European Chapter of the Association for Computational Linguistics (EACL)Adi Haviv, Ido Cohen, Jacob Gidron, et al.2023 · 62 citations
30. MiMo-V2-Flash Technical ReportarXiv:2601.02780Xiaomi LLM-Core Team; Bangjun Xiao; Bingquan Xia; Bo Yang; Bofei Gao; Bowen Shen; Chen Zhang; Chenhong He; Chiheng Lou; Fuli Luo; Gang Wang; Gang Xie; Hailin Zhang; Hanglong Lv; Hanyu Li; Heyu Chen; Hongshen Xu; Houbin Zhang; Huaqiu Liu; Jiangshan Duo; Jianyu Wei; Jiebao Xiao; Jinhao Dong; Jun Shi; Junhao Hu; Kainan Bao; Kang Zhou; Lei Li; Liang Zhao; Linghao Zhang; Peidian Li; Qianli Chen; Shaohui Liu; Shihua Yu; Shijie Cao; Shimao Chen; Shouqiu Yu; Shuo Liu; Tianling Zhou; Weijiang Su; Weikun Wang; Wenhan Ma; Xiangwei Deng; Bohan Mao; Bowen Ye; Can Cai; Chenghua Wang; Chengxuan Zhu; Chong Ma; Chun Chen; Chunan Li; Dawei Zhu; Deshan Xiao; Dong Zhang; Duo Zhang; Fangyue Liu; Feiyu Yang; Fengyuan Shi; Guoan Wang; Hao Tian; Hao Wu; Heng Qu; Hongfei Yi; Hongxu An; Hongyi Guan; Xing Zhang; Yifan Song; Yihan Yan; Yihao Zhao; Yingchun Lai; Yizhao Gao; Yu Cheng; Yuanyuan Tian; Yudong Wang; Zhen Tang; Zhengju Tang; Zhengtao Wen; Zhichao Song; Zhixian Zheng; Zihan Jiang; Jian Wen; Jiarui Sun; Jiawei Li; Jinlong Xue; Jun Xia; Kai Fang; Menghang Zhu; Nuo Chen; Qian Tu; Qihao Zhang; Qiying Wang; Rang Li; Rui Ma; Shaolei Zhang; Shengfan Wang; Shicheng Li; Shuhao Gu; Shuhuai Ren; Sirui Deng; Tao Guo; Tianyang Lu; Weiji Zhuang; Weikang Zhang; Weimin Xiong; Wenshan Huang; Wenyu Yang; Xin Zhang; Xing Yong; Xu Wang; Xueyang Xie; Yilin Jiang; Yixin Yang; Yongzhe He; Yu Tu; Yuanliang Dong; Yuchen Liu; Yue Ma; Yue Yu; Yuxing Xiang; Zhaojun Huang; Zhenru Lin; Zhipeng Xu; Zhiyang Chen; Zhonghua Deng; Zihan Zhang;, Zihao Yue2026 · 60 citations
31. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
32. Kimi Linear: An Expressive, Efficient Attention ArchitecturearXiv:2510.26692Kimi Team, Yu Zhang, Zongyu Lin, et al.2025 · 51 citations
33. Future Lens: Anticipating Subsequent Tokens from a Single Hidden StateConference on Computational Natural Language Learning (CoNLL)Koyena Pal, Jiuding Sun, Andrew Yuan, et al.2023 · 49 citations
34. Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zihan Qiu, Zeyu Huang, Bo Zheng, et al.2025 · 21 citations
35. GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity?arXiv:2502.05252Yang Zhou, Hongyi Liu, Zhuoming Chen, et al.2025 · 21 citations
36. Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUsarXiv:2505.04519Yehui Tang, Yichun Yin, Yaoyuan Wang, et al.2025 · 8 citations
37. FAME: Fictional Actors for Multilingual ErasureLanguage Resources and Evaluation Conference (LREC)Claudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.2026 · 7 citations
38. Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Wenbin Hu, Haoran Li, Huihao Jing, et al.2025 · 7 citations
39. MoM: Linear Sequence Modeling with Mixture-of-MemoriesarXiv:2502.13685Jusen Du, Weigao Sun, Disen Lan, et al.2025 · 7 citations
40. Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?International Joint Conference on Natural Language Processing (IJCNLP)Kai Yan, Yufei Xu, Zhengyin Du, et al.2025 · 5 citations
41. HiddenGuard: Fine-Grained Safe Generation with Specialized Representation RouterAnnual Meeting of the Association for Computational Linguistics (ACL)Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.2026 · 4 citations
42. Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUsarXiv:2503.05139Ling Team; Binwei Zeng; Chao Huang; Chao Zhang; Changxin Tian; Cong Chen; Dingnan Jin; Feng Yu; Feng Zhu; Feng Yuan; Fakang Wang; Gangshan Wang; Guangyao Zhai; Haitao Zhang; Huizhong Li; Jun Zhou; Jia Liu; Junpeng Fang; Junjie Ou; Jun Hu; Ji Luo; Ji Zhang; Jian Liu; Jian Sha; Jianxue Qian; Jiewei Wu; Junping Zhao; Jianguo Li; Jubao Feng; Jingchao Di; Junming Xu; Jinghua Yao; Kuan Xu; Kewei Du; Longfei Li; Lei Liang; Lu Yu; Li Tang; Lin Ju; Peng Xu; Qing Cui; Song Liu; Shicheng Li; Shun Song; Song Yan; Tengwei Cai; Tianyi Chen; Ting Guo; Ting Huang; Tao Feng; Tao Wu; Wei Wu; Xiaolu Zhang; Xueming Yang; Xin Zhao; Xiaobo Hu; Xin Lin; Yao Zhao; Yilong Wang; Yongzhen Guo; Yuanyuan Wang; Yue Yang; Yang Cao; Yuhao Fu; Yi Xiong; Yanzhe Li; Zhe Li; Zhiqiang Zhang; Ziqi Liu; Zhaoxin Huan; Zujie Wen; Zhenhang Sun; Zhuoxuan Du;, Zhengyu He2025 · 4 citations
43. Too Good to be Bad: On the Failure of LLMs to Role-Play VillainsFindings of the Association for Computational LinguisticsZihao Yi, Qingxuan Jiang, Ruotian Ma, et al.2026 · 3 citations
44. a1: Steep Test-time Scaling Law via Environment Augmented GenerationFindings of the Association for Computational LinguisticsLingrui Mei, Shenghua Liu, Yiwei Wang, et al.2026 · 2 citations
45. MiniMax Sparse AttentionarXiv:2606.13392Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.2026 · 2 citations
46. Do LLMs Really Memorize Personally Identifiable Information? Revisiting PII Leakage with a Cue-Controlled Memorization FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Luo, Yiyi Chen, Qiongxiu Li, et al.2026 · 1 citation
47. Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zongyu Wu, Minhua Lin, Zhiwei Zhang, et al.2026 · 1 citation
48. Personal Information Parroting in Language ModelsFindings of the Association for Computational LinguisticsNishant Subramani, Kshitish Ghate, Mona T. Diab2026 · 1 citation
49. PRISP: Privacy-Safe Few-Shot Personalization via Lightweight AdaptationAnnual Meeting of the Association for Computational Linguistics (ACL)Junho Park, Dohoon Kim, Taesup Moon2026 · 1 citation
50. StateX: Enhancing RNN Recall via Post-training State ExpansionFindings of the Association for Computational LinguisticsXingyu Shen, Yingfa Chen, Zhen Leng Thai, et al.2026 · 1 citation
51. The Model's Language Matters: A Comparative Privacy Analysis of LLMsFindings of the Association for Computational LinguisticsAbhishek Kumar Mishra, Antoine Boutet, Lucas Magnana2026 · 1 citation
52. Data Foundations of Long-Context Language Models: A SurveyTransactions of the Association for Computational Linguistics (TACL)Zechen Sun, Yuyang Sun, Zhaochen Su, et al.2026
53. EL-MIA: Quantifying Membership Inference Risks of Sensitive Entities in LLMsLanguage Resources and Evaluation Conference (LREC)Ali Satvaty, Suzan Verberne, Fatih Turkmen2026
54. Exploring Cross-Client Memorization of Training Data in Large Language Models for Federated LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Tinnakit Udsa, Can Udomcharoenchaikit, Patomporn Payoungkhamdee, et al.2026
55. GPT-NL Public Corpus: A Permissively Licensed, Dutch-First Dataset for LLM Pre-trainingLanguage Resources and Evaluation Conference (LREC)Jesse J. Van Oort, Frank Brinkkemper, Erik de Graaf, et al.2026
56. Investigating Memorization in Language Models Trained via Knowledge DistillationLanguage Resources and Evaluation Conference (LREC)Maarten Mäcking, Michaela Regneri2026
57. Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI GroundingAnnual Meeting of the Association for Computational Linguistics (ACL)Wenkai Wang, Xiyun Li, Hongcan Guo, et al.2026
58. Mitigating Coordinate Prediction Bias from Positional Encoding FailuresFindings of the Association for Computational LinguisticsXingjian Tao, Yiwei Wang, Yujun Cai, et al.2026
59. Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and ReasoningFindings of the Association for Computational LinguisticsCong Wan, Ying He, Zhongzhan Huang, et al.2026

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