Peng Li is a Research Associate Professor at Institute for AI Industry Research (AIR), Tsinghua University. He received his B.S. degree in computer science and technology from Tsinghua University in 2009 and his Ph.D. in computer science and technology from Tsinghua University in 2015. Before joining Tsinghua, he was a principal researcher and team leader at WeChat AI, Tencent. He also previously worked at Institute of Deep Learning, Baidu Inc. His main research interests include natural language processing, pre-trained models, question answering, information extraction, machine translation, and dialogue system. He has published about 60 papers and won the first place on a few highly influential leaderboards. He was the recipient of First Prize of Qian Weichang Chinese Information Processing Science and Technology Award.
Homepage
http://www.lpeng.net
Education
2009-2015 Department of Computer Science and Technology, Tsinghua University Ph.D.
2005-2009 Department of Computer Science and Technology, Tsinghua University B.S.
Career
2022-till now Institute of AI Industrial Research, Tsinghua University Research Associate Professor
2018-2022 Pattern Recognition Center, WeChat AI, Tencent Inc. Principal Researcher, Team Leader
2015-2017 Institute of Deep Learning, Baidu Inc. Senior R&D Engineer
Research Fields
Natural language processing, pre-trained models, question answering, information extraction, machine translation, dialog system
Selected Publications
1. Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li*, Jie Zhou, Xu Sun. Topology-Imbalance Learning for Semi-Supervised Node Classification. In Proceedings of NeurIPS 2021.
2. Yujia Qin, Yankai Lin, Ryuichi Takanobu, Zhiyuan Liu, Peng Li*, Heng Ji, Minlie Huang, Maosong Sun, and Jie Zhou. 2021. ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning. In Proceedings of ACL-IJCNLP 2021, 3350-3363.
3. Ziqi Wang, Xiaozhi Wang, Xu Han, Yankai Lin, Lei Hou, Zhiyuan Liu, Peng Li*, Juanzi Li, and Jie Zhou. 2021. CLEVE: Contrastive Pre-training for Event Extraction. In Proceedings of ACL-IJCNLP 2021, 6283-6297.
4. Qiu Ran, Yankai Lin, Peng Li*, and Jie Zhou. 2021. Guiding Non-Autoregressive Neural Machine Translation Decoding with Reordering Information. In Proceedings of AAAI 2021, 13727-13735.
5. Deli Chen, Yankai Lin, Wei Li, Peng Li*, Jie Zhou, and Xu Sun. 2020. Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View. In Proceedings of AAAI 2020, 3438-3445.
6. Qiu Ran, Yankai Lin, Peng Li*, and Jie Zhou. 2020. Learning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation. In Proceedings of ACL 2020, 3059–3069.
7. Qiu Ran, Yankai Lin, Peng Li*, Jie Zhou, and Zhiyuan Liu. 2019. NumNet: Machine Reading Comprehension with Numerical Reasoning. In Proceedings of EMNLP 2019, 2474-2484.
8. Yuan Yao, Deming Ye, Peng Li*, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, and Maosong Sun. 2019. DocRED: A Large-Scale Document-Level Relation Extraction Dataset. In Proceedings of ACL 2019, 764-777.
9. Peng Li*, Yang Liu, and Maosong Sun. 2013. Recursive Autoencoders for ITG-based Translation. In Proceedings of EMNLP 2013, 567-577.
10. Zhiyuan Liu, Peng Li*, Yabin Zheng, and Maosong Sun. 2009. Clustering to Find Exemplar Terms for Keyphrase Extraction. In Proceedings of EMNLP 2009, 257-266.
Major Honors and Awards
2020 First Prize of Qian Weichang Chinese Information Processing Science and Technology Award, Chinese Information Processing Society of China
