Peng Li

Peng Li is a Research Associate Professor at Institute for AI Industry Research (AIR), Tsinghua University, China. 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 (IDL), Baidu Inc. His research interests include artificial intelligence and natural language processing. He received ACL 2023 Outstanding Paper Award, CIKM 2021 Best Resource Paper Nomination, and First Prize of Qian Weichang Chinese Information Processing Science and Technology Award.

Publications & Preprints

2024

• Zonghan Yang, An Liu, Zijun Liu, Kaiming Liu, Fangzhou Xiong, Yile Wang, Zeyuan Yang, Qingyuan Hu, Xinrui Chen, Zhenhe Zhang, Fuwen Luo, Zhicheng Guo, Peng Li, Yang Liu. 2024.
  Position: Towards Unified Alignment Between Agents, Humans, and Environment.
  In Proceedings of ICML 2024, 56251-56275. [pdf] [arXiv] [Project Webpage]
• Sijie Cheng, Zhicheng Guo, Jingwen Wu, Kechen Fang, Peng Li, Huaping Liu, Yang Liu. 2024.
  EgoThink: Evaluating First-Person Perspective Thinking Capability of Vision-Language Models.
  In Proceedings of CVPR 2024, 14291-14302. [pdf] [arXiv] [code] [Project Webpage]
• Fuwen Luo, Chi Chen, Zihao Wan, Zhaolu Kang, Qidong Yan, Yingjie Li, Xiaolong Wang, Siyu Wang, Ziyue Wang, Xiaoyue Mi, Peng Li, Ning Ma, Maosong Sun, Yang Liu. 2024.
  CODIS: Benchmarking Context-Dependent Visual Comprehension for Multimodal Large Language Models.
  In Proceedings of ACL 2024, 10639-10659. [pdf] [arXiv] [code] [Project Webpage]
• Ziyue Wang, Chi Chen, Yiqi Zhu, Fuwen Luo, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Maosong Sun, Yang Liu. 2024.
  Browse and Concentrate: Comprehending Multimodal Content via prior-LLM Context Fusion.
  In Proceedings of ACL 2024, 11229-11245. [pdf] [arXiv] [code]
• Chi Chen, Yiyang Du, Zheng Fang, Ziyue Wang, Fuwen Luo, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Maosong Sun, Yang Liu. 2024.
  Model Composition for Multimodal Large Language Models.
  In Proceedings of ACL 2024, 11246-11262. [pdf] [arXiv] [code]
• Yuanchi Zhang, Yile Wang, Zijun Liu, Shuo Wang, Xiaolong Wang, Peng Li, Maosong Sun, Yang Liu. 2024.
  Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages.
  In Proceedings of ACL 2024, 11189-11204. [pdf] [arXiv] [code]
• Xiaolong Wang, Yile Wang, Yuanchi Zhang, Fuwen Luo, Peng Li, Maosong Sun, Yang Liu. 2024.
  Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models.
  In Proceedings of ACL 2024, 15880-15893. [pdf] [arXiv]
• Zhicheng Guo, Sijie Cheng, Hao Wang, Shihao Liang, Yujia Qin, Peng Li, Zhiyuan Liu, Maosong Sun, Yang Liu. 2024.
  StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models.
  In Findings of ACL 2024, 11143-11156. [pdf] [arXiv] [code] [Project Webpage]
• An Liu, Zonghan Yang, Zhenhe Zhang, Qingyuan Hu, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu. 2024.
  PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs.
  In Findings of ACL 2024, 10960-10977. [pdf] [arXiv] [code]
• Yuanhang Zheng, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu. 2024.
  Budget-Constrained Tool Learning with Planning.
  In Findings of ACL 2024, 9039-9052. [pdf] [arXiv]
• Xiaolong Wang, Yile Wang, Sijie Cheng, Peng Li, Yang Liu. 2024.
  DEEM: Dynamic Experienced Expert Modeling for Stance Detection.
  In Proceedings of COLING 2024, 4530-4541. [pdf] [arXiv] [code]
• Yuanhang Zheng, Peng Li, Wei Liu, Yang Liu, Jian Luan, Bin Wang. 2024.
  ToolRerank: Adaptive and Hierarchy-Aware Reranking for Tool Retrieval.
  In Proceedings of COLING 2024, 16263-16273. [pdf] [arXiv] [code]
• Yuzhuang Xu, Shuo Wang, Peng Li, Xuebo Liu, Xiaolong Wang, Weidong Liu, Yang Liu. 2024.
  Pluggable Neural Machine Translation Models via Memory-augmented Adapters.
  In Proceedings of COLING 2024, 12794-12808. [pdf] [arXiv] [code]
• Zonghan Yang, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu. 2024.
  ReAct Meets ActRe: Autonomous Annotation of Agent Trajectories for Contrastive Self-Training.
  In Proceedings of COLM 2024. [pdf] [arXiv]
• Zijun Liu, Yanzhe Zhang, Peng Li, Yang Liu, Diyi Yang. 2024.
  A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration.
  In Proceedings of COLM 2024. [pdf] [arXiv] [code]
• Yuanhang Zheng, Zhixing Tan, Peng Li, Yang Liu. 2024.
  Black-box Prompt Tuning with Subspace Learning.
  IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2024(32):3002-3013. [pdf] [arXiv]
• Yujia Qin, Xiaozhi Wang, Yusheng Su, Yankai Lin, Ning Ding, Jing Yi, Weize Chen, Zhiyuan Liu, Juanzi Li, Lei Hou, Peng Li, Maosong Sun, Jie Zhou. 2024.
  Exploring Universal Intrinsic Task Subspace for Few-shot Learning via Prompt Tuning.
  IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2024(32):3631-3643. [pdf] [arXiv]
• Xiaoyue Mi, Fan Tang, Yepeng Weng, Danding Wang, Juan Cao, Sheng Tang, Peng Li, Yang Liu. 2024.
  Topology-preserving Adversarial Training for Alleviating Natural Accuracy Degradation.
  To appear in Proceedings of BMVC 2024.
• Tianyuan Zou, Yang Liu, Peng Li, Jianqing Zhang, Jingjing Liu, Ya-Qin Zhang. 2024.
  FuseGen: PLM Fusion for Data-generation based Zero-shot Learning.
  In Proceedings of EMNLP 2024, 2172-2190. [pdf] [arXiv] [code]
• Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, Yunxin Liu. 2024.
  Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security.
  Preprint [arXiv] [Paper List]
• Xuanyu Lei, Zonghan Yang, Xinrui Chen, Peng Li, Yang Liu. 2024.
  Scaffolding Coordinates to Promote Vision-Language Coordination in Large Multi-Modal Models.
  Wordplay Workshop @ ACL 2024. [arXiv] [Project Webpage]
• Zijun Liu, Boqun Kou, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu. 2024.
  Enabling Weak LLMs to Judge Response Reliability via Meta Ranking.
  Preprint [arXiv] [code]
• Ziyue Wang, Chi Chen, Fuwen Luo, Yurui Dong, Yuanchi Zhang, Yuzhuang Xu, Xiaolong Wang, Peng Li, Yang Liu. 2024.
  ActiView: Evaluating Active Perception Ability for Multimodal Large Language Models.
  Preprint [arXiv] [code]
• Wei Zhang, Pengfei Li, Junli Wang, Bingchuan Sun, Qihao Jin, Guangjun Bao, Shibo Rui, Yang Yu, Wenchao Ding, Peng Li, Yilun Chen. 2024.
  Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Braking.
  Preprint [arXiv] [code]
• Junming Lin, Zheng Fang, Chi Chen, Zihao Wan, Fuwen Luo, Peng Li, Yang Liu, Maosong Sun. 2024.
  StreamingBench: Assessing the Gap for MLLMs to Achieve Streaming Video Understanding.
  Preprint [arXiv] [code] [Project Webpage]
• Yile Wang, Sijie Cheng, Zixin Sun, Peng Li, Yang Liu. 2024.
  Speak It Out: Solving Symbol-Related Problems with Symbol-to-Language Conversion for Language Models.
  ICLR AGI Workshop 2024. [arXiv] [code]
• Xiaoyue Mi, Fan Tang, Juan Cao, Peng Li, Yang Liu. 2024.
  Visual-Friendly Concept Protection via Selective Adversarial Perturbations.
  Preprint [arXiv]

2023

• Zeyuan Yang, Peng Li, Yang Liu. 2023.
  Failures Pave the Way: Enhancing Large Language Models through Tuning-free Rule Accumulation.
  In Proceedings of EMNLP 2023, 1751-1777. [pdf] [arXiv] [code]
• Kaiyu Huang, Peng Li, Junpeng Liu, Maosong Sun, Yang Liu. 2023.
  Learn and Consolidate: Continual Adaptation for Zero-Shot and Multilingual Neural Machine Translation.
  In Proceedings of EMNLP 2023, 13938-13951. [pdf] [code]
• Xuanhong Li, Peng Li, Po Hu. 2023.
  Revisiting Source Context in Nearest Neighbor Machine Translation.
  In Proceedings of EMNLP 2023, 8087-8098. [pdf] [code]
• Yile Wang, Peng Li, Maosong Sun, Yang Liu. 2023.
  Self-Knowledge Guided Retrieval Augmentation for Large Language Models.
  In Findings of EMNLP 2023, 10303-10315. [pdf] [arXiv] [code]
• Ziyue Wang, Chi Chen, Peng Li, Yang Liu. 2023.
  Filling the Image Information Gap for VQA: Prompting Large Language Models to Proactively Ask Questions.
  In Findings of EMNLP 2023, 2874-2890. [pdf] [arXiv] [code]
• Yuzhuang Xu, Shuo Wang, Peng Li, Fuwen Luo, Xiaolong Wang, Weidong Liu and Yang Liu. 2023.
  Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf.
  Preprint [arXiv] [code]
• Chi Chen, Ruoyu Qin, Fuwen Luo, Xiaoyue Mi, Peng Li, Maosong Sun, Yang Liu. 2023.
  Position-Enhanced Visual Instruction Tuning for Multimodal Large Language Models.
  Preprint [arXiv] [code] [Demo]
• Kaiyu Huang, Peng Li, Jin Ma, Ting Yao, Yang Liu. 2023.
  Knowledge Transfer in Incremental Learning for Multilingual Neural Machine Translation.
  In Proceedings of ACL 2023, 15286-15304. [pdf] [code]
  (ACL 2023 Outstanding Paper Award)
• Qinhong Zhou, Zonghan Yang, Peng Li, Yang Liu. 2023.
  Bridging the Gap between Decision and Logits in Decision-based Knowledge Distillation for Pre-trained Language Models.
  In Proceedings of ACL 2023, 13234-13248. [pdf] [arXiv] [code]
• Chi Chen, Peng Li, Maosong Sun, Yang Liu. 2023.
  Weakly Supervised Vision-and-Language Pre-training with Relative Representations.
  In Proceedings of ACL 2023, 8341-8355. [pdf] [arXiv] [code]
• Xuancheng Huang, Zijun Liu, Peng Li, Tao Li, Maosong Sun, Yang Liu. 2023.
  An Extensible Plug-and-Play Method for Multi-Aspect Controllable Text Generation.
  In Proceedings of ACL 2023, 15233-15256. [pdf] [arXiv] [code]
• Yuanchi Zhang, Peng Li, Maosong Sun, Yang Liu. 2023.
  Continual Knowledge Distillation for Neural Machine Translation.
  In Proceedings of ACL 2023, 7978-7996. [pdf] [arXiv] [code]
• Yuanjian Xu, Qi An, Jiahuan Zhang, Peng Li, Zaiqing Nie. 2023.
  Hard Sample Aware Prompt-Tuning.
  In Proceedings of ACL 2023, 12356-12369. [pdf]
• Zhengyan Zhang, Zhiyuan Zeng, Yankai Lin, Huadong Wang, Deming Ye, Chaojun Xiao, Xu Han, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2023.
  Plug-and-Play Knowledge Injection for Pre-trained Language Models.
  In Proceedings of ACL 2023, 10641-10658. [pdf] [arXiv]
• Zhicheng Guo, Sijie Cheng, Yile Wang, Peng Li, Yang Liu. 2023.
  Prompt-Guided Retrieval Augmentation for Non-Knowledge-Intensive Tasks.
  In Findings of ACL 2023, 10896-10912. [pdf] [arXiv]
• Zonghan Yang, Peng Li, Tianyu Pang, Yang Liu. 2023.
  Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics.
  In Proceedings of ICML 2023, 39349-39364. [pdf] [arXiv] [code]
• Zonghan Yang, Xiaoyuan Yi, Peng Li, Yang Liu, Xing Xie. 2023.
  Unified Detoxifying and Debiasing in Language Generation via Inference-time Adaptive Optimization.
  In Proceedings of ICLR 2023. [pdf] [arXiv]
• Fengran Mo, Jian-Yun Nie, Kaiyu Huang, Kelong Mao, Yutao Zhu, Peng Li, Yang Liu. 2023.
  Learning to Relate to Previous Turns in Conversational Search.
  In Proceedings of KDD 2023, 1722-1732. [pdf] [arXiv]
• Jifan Yu, Hanming Li, Gan Luo, Yankai Lin, Peng Li, Jianjun Xu, Lei Hou, Bin Xu. 2023.
  Exploring the Effectiveness of Student Behavior in Prerequisite Relation Discovery for Concepts.
  In Proceedings of APWeb-WAIM 2023.
• Wenkai Yang, Yankai Lin, Guangxiang Zhao, Peng Li, Jie Zhou, Xu Sun. 2023.
  When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning.
  Transactions on Machine Learning Research (TMLR), 2023:2835-8856. [pdf] [arXiv] [code]
• Yile Wang, Yue Zhang, Peng Li, Yang Liu. 2023.
  Gradual Syntactic Label Replacement for Language Model Pre-training.
  IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2023(32):486-496. [pdf]
• Qinhong Zhou, Peng Li, Yang Liu, Yuyang Guan, Qizhou Xing, Ming Chen, Maosong Sun, Yang Liu. 2023.
  AdaDS: Adaptive Data Selection for Accelerating Pre-trained Language Model Knowledge Distillation.
  AI Open, 2023(4):56-63. [pdf]
• Zeyuan Yang, Zonghan Yang, Yichen Liu, Peng Li, Yang Liu. 2023.
  Restricted Orthogonal Gradient Projection for Continual Learning.
  AI Open, 2023(4):98-110. [pdf] [arXiv]

2022

• Chi Chen, Peng Li, Maosong Sun, Yang Liu. 2022.
  End-to-End Unsupervised Vision-and-Language Pre-training with Referring Expression Matching.
  In Proceedings of EMNLP 2022, 10799-10810. [pdf] [code]
• Shuo Wang, Peng Li, Zhixing Tan, Zhaopeng Tu, Maosong Sun, Yang Liu. 2022.
  A Template-based Method for Constrained Neural Machine Translation.
  In Proceedings of EMNLP 2022, 3665-3679. [pdf] [arXiv] [code]
• Kaiyu Huang, Peng Li, Jin Ma, Yang Liu. 2022.
  Entropy-Based Vocabulary Substitution for Incremental Learning in Multilingual Neural Machine Translation.
  In Proceedings of EMNLP 2022, 10537-10550. [pdf] [code]
• Lan Jiang, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou, Rui Jiang. 2022.
  ROSE: Robust Selective Fine-tuning for Pre-trained Language Models.
  In Proceedings of EMNLP 2022, 2886-2897. [pdf] [arXiv] [code]
• Xiaozhi Wang, Yulin Chen, Ning Ding, Hao Peng, Zimu Wang, Yankai Lin, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu, Peng Li, Jie Zhou. 2022.
  MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal and Subevent Relation Extraction.
  In Proceedings of EMNLP 2022, 926-941. [pdf] [arXiv] [code]
• Lei Li, Yankai Lin, Xuancheng Ren, Guangxiang Zhao, Peng Li, Jie Zhou, Xu Sun. 2022.
  From Mimicking to Integrating: Knowledge Integration for Pre-Trained Language Models.
  In Findings of EMNLP 2022, 6420-6431. [pdf] [arXiv] [code]
• Jiaxin Mi, Po Hu, Peng Li. 2022.
  Event Detection with Dual Relational Graph Attention Networks.
  In Proceedings of COLING 2022, 1979-1989. [pdf] [code]
• Deli Chen, Yankai Lin, Lei Li, Xuancheng Ren, Peng Li, Jie Zhou, Xu Sun. 2022.
  Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification.
  In Proceedings of IJCAI-22, 2852-2858. [pdf] [arXiv]
• Yujia Qin, Yankai Lin, Jing Yi, Jiajie Zhang, Xu Han, Zhengyan Zhang, Yusheng Su, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2022.
  Knowledge Inheritance for Pre-trained Language Models.
  In Proceedings of NAACL 2022, 3921-3937. [pdf] [arXiv] [code]
• Yusheng Su, Xiaozhi Wang, Yujia Qin, Chi-Min Chan, Yankai Lin, Huadong Wang, Kaiyue Wen, Zhiyuan Liu, Peng Li, Juanzi Li, Lei Hou, Maosong Sun, Jie Zhou. 2022.
  On Transferability of Prompt Tuning for Natural Language Processing.
  In Proceedings of NAACL 2022, 3949-3969. [pdf] [arXiv] [code]
• Weize Chen, Xu Han, Yankai Lin, Hexu Zhao, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2022.
  Fully Hyperbolic Neural Networks.
  In Proceedings of ACL 2022, 5672-5686. [pdf] [arXiv] [code]
• Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron Courville. 2022.
  Unsupervised Dependency Graph Network.
  In Proceedings of ACL 2022, 4767-4784. [pdf]
• Deming Ye, Yankai Lin, Peng Li, Maosong Sun. 2022.
  Packed Levitated Marker for Entity and Relation Extraction.
  In Proceedings of ACL 2022, 4904-4917. [pdf] [arXiv] [code]
• Pei Ke, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou, Xiaoyan Zhu, Minlie Huang. 2022.
  CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation.
  In Proceedings of ACL 2022, 2306-2319. [pdf] [arXiv] [code]
• Deming Ye, Yankai Lin, Peng Li, Maosong Sun, Zhiyuan Liu. 2022.
  A Simple but Effective Pluggable Entity Lookup Table for Pre-trained Language Models.
  In Proceedings of ACL 2022 (short), 523-529. [pdf] [arXiv] [code]
• Yujia Qin, Jiajie Zhang, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2022.
  ELLE: Efficient Lifelong Pre-training for Emerging Data.
  In Findings of ACL 2022, 2789-2810. [pdf] [arXiv] [code]
• Xin Lv, Yankai Lin, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Peng Li, Jie Zhou. 2022.
  Do Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach.
  In Findings of ACL 2022, 3570-3581. [pdf] [code]
• Zhengyan Zhang, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2022.
  MoEfication: Transformer Feed-forward Layers are Mixtures of Experts.
  In Findings of ACL 2022, 877-890. [pdf] [arXiv] [code]
• Ryuichi Takanobu, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou, Minlie Huang. 2022.
  Manual-Guided Dialogue for Flexible Conversational Agents.
  Preprint [arXiv]

2021

• Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li, Jie Zhou, Xu Sun. 2021.
  Topology-Imbalance Learning for Semi-Supervised Node Classification.
  In Proceedings of NeurIPS 2021. [pdf] [code]
• Lei Li, Yankai Lin, Shuhuai Ren, Peng Li, Jie Zhou, Xu Sun. 2021.
  Dynamic Knowledge Distillation for Pre-trained Language Models.
  In Proceedings of EMNLP 2021, 379-389. [pdf] [code]
• Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, Xu Sun. 2021.
  RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models.
  In Proceedings of EMNLP 2021, 8365-8381. [pdf] [arXiv]
• Yuan Yao, Jiaju Du, Yankai Lin, Peng Li, Zhiyuan Liu, Jie Zhou, Maosong Sun. 2021.
  CodRED: A Cross-Document Relation Extraction Dataset for Acquiring Knowledge in the Wild.
  In Proceedings of EMNLP 2021, 4452-4472. [pdf] [code & data] [Leaderboard]
• Lei Li, Yankai Lin, Deli Chen, Shuhuai Ren, Peng Li, Jie Zhou, Xu Sun. 2021.
  CascadeBERT: Accelerating Inference of Pre-trained Language Models via Calibrated Complete Models Cascade.
  In Findings of EMNLP 2021, 475-486. [pdf] [code]
• Jifan Yu, Yuquan Wang, Qingyang Zhong, Gan Luo, Yiming Mao, Kai Sun, Wenzheng Feng, Wei Xu, Shulin Cao, Kaisheng Zeng, Zijun Yao, Lei Hou, Yankai Lin, Peng Li, Jie Zhou, Bin Xu, Juanzi Li, Jie Tang, Maosong Sun. 2021.
  MOOCCubeX: A Large Knowledge-centered Repository for Adaptive Learning in MOOCs.
  In Proceedings of CIKM 2021, 4643-4652. [pdf] [code]
  (CIKM 2021 Best Resource Paper Nomination)
• Yusheng Su, Xu Han, Zhengyan Zhang, Peng Li, Zhiyuan Liu, Yankai Lin, Jie Zhou, Maosong Sun. 2021.
  CokeBERT: Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models.
  AI Open, 2021(2):127-134. [pdf] [code]
• Yujia Qin, Yankai Lin, Ryuichi Takanobu, Zhiyuan Liu, Peng Li, Heng Ji, Minlie Huang, Maosong Sun, 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. [pdf] [code]
• Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, Xu Sun. 2021.
  Rethinking Stealthiness of Backdoor Attack against NLP Models.
  In Proceedings of ACL-IJCNLP 2021, 5543-5557. [pdf] [code]
• Ziqi Wang, Xiaozhi Wang, Xu Han, Yankai Lin, Lei Hou, Zhiyuan Liu, Peng Li, Juanzi Li, Jie Zhou. 2021.
  CLEVE: Contrastive Pre-training for Event Extraction.
  In Proceedings of ACL-IJCNLP 2021, 6283-6297. [pdf] [code]
• Feilong Chen, Xiuyi Chen, Fandong Meng, Peng Li, Jie Zhou. 2021.
  GoG: Relation-aware Graph-over-Graph Network for Visual Dialog.
  In Findings of ACL-IJCNLP 2021, 230-243. [pdf]
• Feilong Chen, Fandong Meng, Xiuyi Chen, Peng Li, Jie Zhou. 2021.
  Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation.
  In Findings of ACL-IJCNLP 2021, 436-446. [pdf]
• Xiuyi Chen, Feilong Chen, Fandong Meng, Peng Li, Jie Zhou. 2021.
  Unsupervised Knowledge Selection for Dialogue Generation.
  In Findings of ACL-IJCNLP 2021, 1230-1244. [pdf]
• Tianyu Gao, Xu Han, Yuzhuo Bai, Keyue Qiu, Zhiyu Xie, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2021.
  Manual Evaluation Matters: Reviewing Test Protocols of Distantly Supervised Relation Extraction.
  In Findings of ACL-IJCNLP 2021, 1306-1318. [pdf] [code]
• Huimin Chen, Yankai Lin, Fanchao Qi, Jinyi Hu, Peng Li, Jie Zhou, Maosong Sun. 2021.
  Aspect-Level Sentiment-Controllable Review Generation with Mutual Learning Framework.
  In Proceedings of AAAI 2021, 12639-12647. [pdf]
• Qiu Ran*, Yankai Lin*, Peng Li*, Jie Zhou. 2021.
  Guiding Non-Autoregressive Neural Machine Translation Decoding with Reordering Information.
  In Proceedings of AAAI 2021, 13727-13735. [pdf] [code]
• Yingxue Zhang, Fandong Meng, Peng Li, Ping Jian, Jie Zhou. 2021.
  Context Tracking Network: Graph-based Context Modeling for Implicit Discourse Relation Recognition.
  In Proceedings of NAACL 2021 (short), 1592–1599. [pdf] [code]
• Yusheng Su, Xu Han, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Peng Li, Jie Zhou, Maosong Sun. 2021.
  CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of Pre-trained Language Models.
  IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2021(29):2930-2941. [pdf] [code]
• Xianfeng Zeng, Yijin Liu, Ernan Li, Qiu Ran, Fandong Meng, Peng Li, Jinan Xu, Jie Zhou. 2021.
  WeChat Neural Machine Translation Systems for WMT21.
  In Proceedings of WMT21, 243–254. [pdf]
• Yingxue Zhang, Fandong Meng, Peng Li, Ping Jian, Jie Zhou. 2021.
  MS-Ranker: Accumulating Evidence from Potentially Correct Candidates via Reinforcement Learning for Answer Selection.
  Neurocomputing, 2021(449):270-279. [pdf]

2020

• Xiuyi Chen, Fandong Meng, Peng Li, Feilong Chen, Shuang Xu, Bo Xu, Jie Zhou. 2020.
  Bridging the Gap between Prior and Posterior Knowledge Selection for Knowledge-Grounded Dialogue Generation.
  In Proceedings of EMNLP 2020, 3426–3437. [pdf]
• Hao Peng, Tianyu Gao, Xu Han, Yankai Lin, Peng Li, Zhiyuan Liu, Maosong Sun, Jie Zhou. 2020.
  Learning from Context or Names? An Empirical Study on Neural Relation Extraction.
  In Proceedings of EMNLP 2020, 3661–3672. [pdf] [code]
• Deming Ye, Yankai Lin, Jiaju Du, Zhenghao Liu, Peng Li, Maosong Sun, Zhiyuan Liu. 2020.
  Coreferential Reasoning Learning for Language Representation.
  In Proceedings of EMNLP 2020, 7170–7186. [pdf] [code]
• Xiaoyu Kou, Yankai Lin, Shaobo Liu, Peng Li, Jie Zhou, Yan Zhang. 2020.
  Disentangle-based Continual Graph Representation Learning.
  In Proceedings of EMNLP 2020, 2961-2972. [pdf] [code]
• Xiaozhi Wang, Ziqi Wang, Xu Han, Wangyi Jiang, Rong Han, Zhiyuan Liu, Juanzi Li, Peng Li, Yankai Lin, Jie Zhou. 2020.
  MAVEN: A Massive General Domain Event Detection Dataset.
  In Proceedings of EMNLP 2020, 1652–1671. [pdf] [code]
• Fandong Meng, Jianhao Yan, Yijin Liu, Yuan Gao, Xianfeng Zeng, Qinsong Zeng, Peng Li, Ming Chen, Jie Zhou, Sifan Liu, Hao Zhou. 2020.
  WeChat Neural Machine Translation Systems for WMT20.
  In Proceedings of WMT20, 239–247. [pdf]
• Qiu Ran*, Yankai Lin*, Peng Li*, Jie Zhou. 2020.
  Learning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation.
  In Proceedings of ACL 2020, 3059–3069. [pdf] [code]
• Xu Han, Yi Dai, Tianyu Gao, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2020.
  Continual Relation Learning via Episodic Memory Activation and Reconsolidation.
  In Proceedings of ACL 2020, 6429–6440. [pdf] [code]
• Deli Chen, Yankai Lin, Wei Li, Peng Li, Jie Zhou, 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. [pdf]
• Feilong Chen, Fandong Meng, Jiaming Xu, Peng Li, Bo Xu, Jie Zhou. 2020.
  DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog.
  In Proceedings of AAAI 2020, 7504-7511. [pdf] [code]
• Xiaozhi Wang, Shengyu Jia, Xu Han, Zhiyuan Liu, Juanzi Li, Peng Li, Jie Zhou. 2020.
  Neural Gibbs Sampling for Joint Event Argument Extraction.
  In Proceedings of AACL 2020, 169-180. [pdf] [code]
• Xu Han, Tianyu Gao, Yankai Lin, Hao Peng, Yaoliang Yang, Chaojun Xiao, Zhiyuan Liu, Peng Li, Jie Zhou, Maosong Sun. 2020.
  More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction.
  In Proceedings of AACL 2020, 745-758. [pdf]

2019

• Qiu Ran, Yankai Lin, Peng Li, Jie Zhou, Zhiyuan Liu. 2019.
  NumNet: Machine Reading Comprehension with Numerical Reasoning.
  In Proceedings of EMNLP 2019, 2474-2484. [pdf] [code]
• Xiaozhi Wang, Ziqi Wang, Xu Han, Zhiyuan Liu, Juanzi Li, Peng Li, Maosong Sun, Jie Zhou, Xiang Ren. 2019.
  HMEAE: Hierarchical Modular Event Argument Extraction.
  In Proceedings of EMNLP 2019 (short), 5777–5783. [pdf] [code]
• Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. 2019.
  FewRel 2.0: Towards More Challenging Few-Shot Relation Classification.
  In Proceedings of EMNLP 2019 (short), 6250–6255. [pdf] [code] [benchmark]
• Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, Maosong Sun. 2019.
  DocRED: A Large-Scale Document-Level Relation Extraction Dataset.
  In Proceedings of ACL 2019, 764-777. [pdf] [code & data] [Leaderboard]
• Fuli Luo, Peng Li, Pengcheng Yang, Jie Zhou, Yutong Tan, Baobao Chang, Zhifang Sui, Xu Sun. 2019.
  Towards Fine-grained Text Sentiment Transfer.
  In Proceedings of ACL 2019, 2013-2022. [pdf] [code]
• Shuming Ma, Pengcheng Yang, Tianyu Liu, Peng Li, Jie Zhou, Xu Sun. 2019.
  Key Fact as Pivot: A Two-Stage Model for Low Resource Table-to-Text Generation.
  In Proceedings of ACL 2019, 2047-2057. [pdf] [code]
• Fuli Luo, Peng Li, Jie Zhou, Pengcheng Yang, Baobao Chang, Xu Sun, Zhifang Sui. 2019.
  A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer.
  In Proceedings of IJCAI 2019, 5116-5122. [pdf] [code]
• Xiaozhi Wang, Xu Han, Zhiyuan Liu, Maosong Sun, Peng Li. 2019.
  Adversarial Training for Weakly Supervised Event Detection.
  In Proceedings of NAACL 2019, 998-1008. [pdf] [code]
• Deli Chen, Xiaoqian Liu, Yankai Lin, Peng Li, Jie Zhou, Qi Su, Xu Sun. 2019.
  HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Networks.
  Preprint [arXiv]
• Qiu Ran, Peng Li, Weiwei Hu, Jie Zhou. 2019.
  Option Comparison Network for Multiple-choice Reading Comprehension.
  Preprint [arXiv] [code]

2008~2018

• Xu Han, Pengfei Yu, Zhiyuan Liu, Maosong Sun, Peng Li. 2018.
  Hierarchical Relation Extraction with Coarse-to-Fine Grained Attention.
  In Proceedings of EMNLP 2018, 2236-2245. [pdf] [code]
• Peng Li, Wei Li, Zhengyan He, Xuguang Wang, Ying Cao, Jie Zhou, Wei Xu. 2016.
  Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering.
  Preprint [arXiv] [code (in the directory "neural_qa", veryfied on Ubuntu 16.04 with PaddlePaddle 0.10.5)]
• Jie Zhou, Ying Cao, Xuguang Wang, Peng Li, Wei Xu. 2016.
  Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation.
  Transactions of the Association for Computational Linguistics (TACL), 2016(4):371-383. [pdf]
• Peng Li, Yang Liu, Maosong Sun, Tatsuya Izuha, Dakun Zhang. 2014.
  A Neural Reordering Model for Phrase-based Translation.
  In Proceedings of COLING 2014, 1897-1907. [pdf] [slides]
• Peng Li, Yang Liu, Maosong Sun. 2013.
  Recursive Autoencoders for ITG-based Translation.
  In Proceedings of EMNLP 2013, 567-577. [pdf] [Talk at MSRA Ph.D Forum]
• Peng Li, Yang Liu, Maosong Sun. 2013.
  An Extended GHKM Algorithm for Inducing Lambda-SCFG.
  In Proceedings of AAAI-13, 605-611. [pdf] [slides]
• Peng Li, Yang Liu, Maosong Sun. 2012.
  A Beam Search Algorithm for ITG Word Alignment.
  In Proceedings of COLING 2012: Posters (short), 673-682. [pdf]
• Peng Li, Maosong Sun, Ping Xue. 2010.
  Fast-Champollion: A Fast and Robust Sentence Alignment Algorithm.
  In Proceedings of COLING 2010: Posters, 710-718. [pdf]
• Xiance Si, Zhiyuan Liu, Peng Li, Qixia Jiang, Maosong Sun. 2009.
  Content-based and Graph-based Tag Suggestion.
  In Proceedings of ECML/PKDD 2009 Discovery Challenge Workshop, 243-260. [pdf]
• Zhiyuan Liu, Peng Li, Yabin Zheng, Maosong Sun. 2009.
  Clustering to Find Exemplar Terms for Keyphrase Extraction.
  In Proceedings of EMNLP 2009, 257-266. [pdf]
• Zhiyuan Liu, Peng Li, Yabin Zheng, Maosong Sun. 2008.
  Community Detection by Affinity Propagation.
  Technical Report. [pdf]

Professional Services

• Senior Area Chair: AACL (2022)
• Area Chair: ACL (2024), NAACL (2024), EACL (2024), COLING (2022)
• Action Editor: ACL Rolling Review (ARR)
• PC Chair: YWCL (2010)
• Tutorial Chair: CCL (2023), CCMT (2023)
• Demonstration Chair: CCL (2024)
• Reviewer/PC Member: NeurIPS (2022-2024), ICML (2022-2024), ICLR (2024,2025), ACL (2014, 2021-2023), EMNLP (2014, 2021-2023), NAACL (2018), CVPR (2023-2025), ICCV (2023), ECCV (2024), AAAI (2022-2025), IJCAI (2022-2024), COLING (2020,2024,2025), BMVC (2024), COLM (2024), ICRA (2025), ACM TIST(2015), TACL (Standing Reviewer), Acta Automatica Sinica

Education

• Aug, 2009 - Jan, 2015. Ph.D in Dept. of Computer Science and Technology, Tsinghua University, Beijing, China.
• Aug, 2005 - Jul, 2009. B.S. in Dept. of Computer Science and Technology, Tsinghua University, Beijing, China.

Last-updated: Nov 14, 2024.