Papers

[Google Scholar]

✨ Preprints

• The Hallucination Tax of Reinforcement Finetuning
  Linxin Song*, Taiwei Shi*, Jieyu Zhao
• Discovering Knowledge Deficiencies of Language Models on Massive Knowledge Base
  Linxin Song, Xuwei Ding, Jieyu Zhang, Taiwei Shi, Ryotaro Shimizu, Rahul Gupta, Yang Liu, Jian Kang, Jieyu Zhao
• Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
  Taiwei Shi, Yiyang Wu, Linxin Song, Tianyi Zhou, Jieyu Zhao
• Enhancing Diversity in Text-to-Image Generation without Compromising Fidelity
  Jiazhi Li, Mi Zhou, Mahyar Khayatkhoei, Jingyu Shi, Xiang Gao, Jiageng Zhu, Hanchen Xie, Xiyun Song, Zongfang Lin, Heather Yu, Liang Peng, Jieyu Zhao
• WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback
  Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Jauhar, Sihao Chen, Shan Xia, Hongfei Zhang, Jieyu Zhao, Xiaofeng Xu, Xia Song, Jennifer Neville
• Detecting and Filtering Unsafe Training Data via Data Attribution
  Yijun Pan, Taiwei Shi, Jieyu Zhao, Jiaqi W. Ma
• On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
  Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Yujun Zhou, Yanbo Wang, Jiayi Ye, Jiawen Shi, Qihui Zhang, Yuan Li, Han Bao, Zhaoyi Liu, Tianrui Guan, Dongping Chen, Ruoxi Chen, Kehan Guo, Andy Zou, Bryan Hooi Kuen-Yew, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jaehong Yoon, Jieyu Zhang, Kai Shu, Kaijie Zhu, Ranjay Krishna, Swabha Swayamdipta, Taiwei Shi, Weijia Shi, Xiang Li, Yiwei Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V. Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Xiangliang Zhang

📄 Published

• TrustLLM: Trustworthiness in Large Language Models
  Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, ... , Jieyu Zhao, ..., Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao. ICML 2024.

• A dynamic approach to long-term fairness in sequential decision-making
  Yuancheng Xu, Chenghao Deng, Yanchao Sun, Ruijie Zheng, Xiyao Wang, Jieyu Zhao, Furong Huang. ICML 2024.

• Fair Abstractive Summarization of Diverse Perspectives
  Yusen Zhang, Nan Zhang, Yixin Liu, Alexander Fabbri, Junru Liu, Ryo Kamoi, Xiaoxin Lu, Caiming Xiong, Jieyu Zhao, Dragomir Radev, Kathleen McKeown, Rui Zhang. NAACL 2024.

• Safer-Instruct: Aligning Language Models with Automated Preference Data
  Taiwei Shi, Kai Chen, Jieyu Zhao. NAACL 2024. SeT-LLM 2024.

• A Rose by Any Other Name would not Smell as Sweet: Social Bias in Name Mistranslations
  Sandra Sandoval, Jieyu Zhao, Marine Carpuat, and Hal Daume III. EMNLP 2023.

• Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systems
  Yixin Wan, Jieyu Zhao, Aman Chadha, Nanyun Peng, and Kai-Wei Chang. EMNLP-Finding, 2023.

• Mind What You Measure For: A Study on Reliability of Prompt-Based Bias Measurement
  Ruyuan Zuo, and Jieyu Zhao. WiNLP 2023.

• TACO: Temporal Latent Action-Driven Contrastive Loss For Visual Reinforcement Learning

  Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu, Hal Daume, Furong Huang. NeurIPS, 2023.
  [website][code]

• SODAPOP: Open-Ended Discovery of Social Biases in Social Commonsense Reasoning Models
  Haozhe An, Zongxia Li, Jieyu Zhao, Rachel Rudinger. EACL 2023.
  [code][poster][video]

• Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers
  Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang. EMNLP Findings, 2022.

• On Measures of Biases and Harms in NLP
  Sunipa Dev, Emily Sheng, Jieyu Zhao, Aubrie Amstutz, Jiao Sun, Yu Hou, Mattie Sanseverino, Jiin Kim, Akihiro Nishi, Nanyun Peng, and Kai-Wei Chang. AACL, 2022.

• Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?
  Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, and Kai-Wei Chang. ACL Findings, 2021.

• Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation
  Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, and Cho-Jui Hsieh. NAACL 2021.

• LOGAN: Local Group Bias Detection by Clustering
  Jieyu Zhao and Kai-Wei Chang. EMNLP 2020.

• Fairness-Aware Explainable Recommendation over Knowledge Graphs
  Zuohui Fu*, Yikun Xian*, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo. SIGIR 2020.

• Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
  Jieyu Zhao, Subhabrata Mukherjee, Saghar Hosseini, Kai-Wei Chang, Ahmed Hassan Awadallah.
  Conference of the Association for Computational Linguistics. ACL 2020.

• Mitigating Gender Bias Amplification in Distribution by Posterior Regularization

  Shengyu Jia*, Tao Meng*, Jieyu Zhao, Kai-Wei Chang.

  Conference of the Association for Computational Linguistics. ACL 2020.

• "The Boating Store Had Its Best Sail Ever": Pronunciation-attentive Contextualized Pun Recognition

  Yichao Zhou, Jyun-Yu Jiang, Jieyu Zhao, Kai-Wei Chang, Wei Wang

  Conference of the Association for Computational Linguistics. ACL 2020.

• Towards Understanding Gender Bias in Relation Extraction

  Andrew Gaut, Tony Sun, Shirlyn Tang, Yuxin Huang, Jing Qian, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, and William Yang Wang

  Conference of the Association for Computational Linguistics. ACL 2020.

• Examining Gender Bias in Languages with Grammatical Gender

  Pei Zhou, Weijia Shi, Jieyu Zhao, Kuan-Hao Huang, Muhao Chen, Ryan Cotterell, Kai-Wei Chang.

  Conference on Empirical Methods in Natural Language Processing. EMNLP 2019.

• Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations

  Tianlu Wang, Jieyu Zhao, Mark Yatskar, Kai-Wei Chang, Vicente Ordonez.

  International Conference on Computer Vision. ICCV 2019.

• Mitigating Gender Bias in Natural Language Processing: Literature Review

  Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang.

  Association for Computational Linguistics. ACL 2019.

• Gender Bias in Contextualized Word Embeddings [video] [slides]

  Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, Kai-Wei Chang.

  North American Chapter of the Association for Computational Linguistics. NAACL 2019.

• Learning Gender-Neutral Word Embeddings [code]

  Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, Kai-Wei Chang

  Conference on Empirical Methods in Natural Language Processing. EMNLP 2018.

• Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods [code] [podcast]

  Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.

  North American Chapter of the Association for Computational Linguistics. NAACL 2018.

• Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints [code]

  Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.

  Conference on Empirical Methods in Natural Language Processing. EMNLP 2017. (Best Long Paper Award)

  Press: Wired: Machines Taught By Photos Learn a Sexist View of Women