I’m a postdoctoral researcher in Conversational AI Group, Department of Computer Science and Technology, Tsinghua University, collaborated with Prof. Minlie Huang. Before that, I received my Ph.D. degree in Computer Science and Technology from Tsinghua University, advised by Prof. Xiaoyan Zhu and Prof. Minlie Huang. My research interests include natural language generation, dialogue system, and sentiment analysis.

Education

• 2017.9 - 2022.6: Ph.D., Department of Computer Science and Technology, Tsinghua University
• 2013.9 - 2017.6: B.Eng., Department of Control Science and Engineering, Zhejiang University

Publications

Conference Papers

• Pei Ke, Bosi Wen, Zhuoer Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, Minlie Huang. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation. ACL 2024 (CCF-A, Long Paper).[pdf]
• Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang. Learning Task Decomposition to Assist Humans in Competitive Programming. ACL 2024 (CCF-A, Long Paper).[pdf]
• Xiao Liu, Xuanyu Lei, Shengyuan Wang, Yue Huang, Zhuoer Feng, Bosi Wen, Jiale Cheng, Pei Ke, Yifan Xu, Weng Lam Tam, Xiaohan Zhang, Lichao Sun, Xiaotao Gu, Hongning Wang, Jing Zhang, Minlie Huang, Yuxiao Dong, Jie Tang. AlignBench: Benchmarking Chinese Alignment of Large Language Models. ACL 2024 (CCF-A, Long Paper).[pdf]
• Jiale Cheng, Xiao Liu, Kehan Zheng, Pei Ke, Hongning Wang, Yuxiao Dong, Jie Tang, Minlie Huang. Black-Box Prompt Optimization: Aligning Large Language Models without Model Training. ACL 2024 (CCF-A, Long Paper).[pdf]
• Zhexin Zhang, Junxiao Yang, Pei Ke, Fei Mi, Hongning Wang, Minlie Huang. Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization. ACL 2024 (CCF-A, Long Paper).[pdf]
• Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang. Towards Efficient Exact Optimization of Language Model Alignment. ICML 2024 (CCF-A).[pdf]
• Haozhe Ji, Pei Ke, Hongning Wang, Minlie Huang. Language Model Decoding as Direct Metrics Optimization. ICLR 2024.[pdf]
• Jiaxin Wen, Pei Ke, Hao Sun, Zhexin Zhang, Chengfei Li, Jinfeng Bai, Minlie Huang. Unveiling the Implicit Toxicity in Large Language Models. EMNLP 2023 (CCF-B, Long Paper).[pdf]
• Pei Ke, Fei Huang, Fei Mi, Yasheng Wang, Qun Liu, Xiaoyan Zhu, Minlie Huang. DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question Answering. ACL 2023 (CCF-A, Long Paper).[pdf]
• Chujie Zheng, Pei Ke, Zheng Zhang, Minlie Huang. Click: Controllable Text Generation with Sequence Likelihood Contrastive Learning. ACL 2023 Findings (Long Paper).[pdf]
• Haozhe Ji, Pei Ke, Zhipeng Hu, Rongsheng Zhang, Minlie Huang. Tailoring Language Generation Models under Total Variation Distance. ICLR 2023 (Notable-Top-5%).[pdf]
• Yuxian Gu, Pei Ke, Xiaoyan Zhu, Minlie Huang. Learning Instructions with Unlabeled Data for Zero-Shot Cross-Task Generalization. EMNLP 2022 (CCF-B, Long Paper).[pdf]
• Pei Ke, Haozhe Ji, Zhenyu Yang, Yi Huang, Junlan Feng, Xiaoyan Zhu, Minlie Huang. Curriculum-Based Self-Training Makes Better Few-Shot Learners for Data-to-Text Generation. IJCAI 2022 (CCF-A, Full Paper).[pdf]
• Pei Ke, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou, Xiaoyan Zhu, Minlie Huang. CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation. ACL 2022 (CCF-A, Long Paper).[pdf]
• Siyang Liu, Sahand Sabour, Yinhe Zheng, Pei Ke, Xiaoyan Zhu, Minlie Huang. Rethinking and Refining the Distinct Metric. ACL 2022 (CCF-A, Short Paper).[pdf]
• Pei Ke, Haozhe Ji, Yu Ran, Xin Cui, Liwei Wang, Linfeng Song, Xiaoyan Zhu, Minlie Huang. JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs. ACL 2021 Findings (Long Paper).[pdf]
• Pei Ke, Haozhe Ji, Siyang Liu, Xiaoyan Zhu, Minlie Huang. SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge. EMNLP 2020 (CCF-B, Long Paper).[pdf]
• Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Xiaoyan Zhu, Minlie Huang. Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph. EMNLP 2020 (CCF-B, Long Paper).[pdf]
• Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Minlie Huang. Generating Commonsense Explanation by Extracting Bridge Concepts from Reasoning Paths. AACL 2020 (Long Paper).[pdf]
• Yida Wang, Pei Ke, Yinhe Zheng, Kaili Huang, Yong Jiang, Xiaoyan Zhu, Minlie Huang. A Large-Scale Chinese Short-Text Conversation Dataset. NLPCC 2020 (CCF-C, Best Student Paper).[pdf]
• Pei Ke, Fei Huang, Minlie Huang, Xiaoyan Zhu. ARAML: A Stable Adversarial Training Framework for Text Generation. EMNLP 2019 (CCF-B, Long Paper).[pdf]
• Pei Ke, Jian Guan, Minlie Huang, Xiaoyan Zhu. Generating Informative Responses with Controlled Sentence Function. ACL 2018 (CCF-A, Long Paper).[pdf]

Journal Papers

• Fei Huang, Pei Ke, Minlie Huang. Directed Acyclic Transformer Pre-training for High-quality Non-autoregressive Text Generation. TACL 2023 (CCF-B).[pdf]

Preprints

• Yuxian Gu, Jiaxin Wen, Hao Sun, Yi Song, Pei Ke, Chujie Zheng, Zheng Zhang, Jianzhu Yao, Xiaoyan Zhu, Jie Tang, Minlie Huang. EVA2.0: Investigating Open-Domain Chinese Dialogue Systems with Large-Scale Pre-Training. arXiv preprint 2022.[pdf]
• Hao Zhou, Pei Ke, Zheng Zhang, Yuxian Gu, Yinhe Zheng, Chujie Zheng, Yida Wang, Chen Henry Wu, Hao Sun, Xiaocong Yang, Bosi Wen, Xiaoyan Zhu, Minlie Huang, Jie Tang. EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training. arXiv preprint 2021.[pdf]
• Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan Yao, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun. CPM-2: Large-scale Cost-effective Pre-trained Language Models. arXiv preprint 2021.[pdf]
• Fei Huang, Jian Guan, Pei Ke, Qihan Guo, Xiaoyan Zhu, Minlie Huang. A Text GAN for Language Generation with Non-Autoregressive Generator. OpenReview preprint 2021.[pdf]
• Fei Huang, Dazhen Wan, Zhihong Shao, Pei Ke, Jian Guan, Yilin Niu, Xiaoyan Zhu, Minlie Huang. CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation. arXiv preprint 2020.[pdf]
• Zhengyan Zhang, Xu Han, Hao Zhou, Pei Ke, Yuxian Gu, Deming Ye, Yujia Qin, YuSheng Su, Haozhe Ji, Jian Guan, Fanchao Qi, Xiaozhi Wang, Yanan Zheng, Guoyang Zeng, Huanqi Cao, Shengqi Chen, Daixuan Li, Zhenbo Sun, Zhiyuan Liu, Minlie Huang, Wentao Han, Jie Tang, Juanzi Li, Xiaoyan Zhu, Maosong Sun. CPM: A Large-scale Generative Chinese Pre-trained Language Model. arXiv preprint 2020.[pdf]

Services

• Action Editor: ACL Rolling Review (2023-2024)
• Area Chair: ACL 2023, EMNLP 2023
• Conference Reviewer: ACL (2020-2022), EMNLP (2019, 2021-2022), NAACL 2022, NeurIPS (2020-2024), ICML (2021-2023), ICLR (2022-2024), AAAI (2019-2021)
• Journal Reviewer: ACM TKDD, IEEE TNNLS, IEEE TASLP, IEEE TKDE, ACM TWEB, CL, TACL, ACM TIST, IPM

Teaching

I was a TA for the following undergraduate courses:

• Artificial Neural Network (2017 Fall, 2018 Fall)
• Object-Oriented Programming (2018 Spring, 2019 Spring, 2020 Spring)
• Discrete Mathematics (2017 Fall)

Selected Honors and Awards

• China National Postdoctoral Program for Innovative Talents, 2023
• Excellent Graduate Student from Department of Computer Science and Technology, Tsinghua University, 2022
• Tsinghua-VMWare Scholarship, Tsinghua University, 2021
• 2nd Prize in Comprehensive Scholarship, Tsinghua University, 2020
• Tencent Rhino-Bird Elite Training Program, 2020
• Lixin Tang Scholarship (Top 40 undergraduate students at each year), Zhejiang University, 2016
• Meritorious Winner (Top 8%), Mathematical Contest In Modeling (MCM), 2016
• 1st Prize in National Mathematical Competition for College Students (Non-Professional Group), 2015
• National Scholarship in China (Top 2%), Zhejiang University, 2014, 2015
• 1st Prize in Competition in Physics Innovation, Zhejiang Province, 2014