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 and First Prize of Qian Weichang Chinese Information Processing Science and Technology Award.

Publications

2023

• Zeyuan Yang, Peng Li and 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 and 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 and 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 and 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 and 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]
• Chi Chen, Ruoyu Qin, Fuwen Luo, Xiaoyue Mi, Peng Li, Maosong Sun and Yang Liu. 2023.
  Position-Enhanced Visual Instruction Tuning for Multimodal Large Language Models.
  Preprint [arXiv] [code] [Demo]
• Zijun Liu, Yanzhe Zhang, Peng Li, Yang Liu and Diyi Yang. 2023.
  Dynamic LLM-Agent Network: An LLM-agent Collaboration Framework with Agent Evaluation.
  Preprint [arXiv] [code]
• Kaiyu Huang, Peng Li, Jin Ma, Ting Yao and 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)
• Qinhong Zhou, Zonghan Yang, Peng Li and 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 and 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 and 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 and 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 and 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 and 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 and 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 and 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 and 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 and 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 and Bin Xu. 2023.
  Exploring the Effectiveness of Student Behavior in Prerequisite Relation Discovery for Concepts.
  To appear in Proceedings of APWeb-WAIM 2023.
• Wenkai Yang, Yankai Lin, Guangxiang Zhao, Peng Li, Jie Zhou and 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 and 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 and 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 and Yang Liu. 2023.
  Restricted Orthogonal Gradient Projection for Continual Learning.
  AI Open, 2023(4):98-110. [pdf]
• Yuanhang Zheng, Zhixing Tan, Peng Li and Yang Liu. 2023.
  Black-box Prompt Tuning with Subspace Learning.
  Preprint [arXiv]
• Yuzhuang Xu, Shuo Wang, Peng Li, Xuebo Liu, Xiaolong Wang, Weidong Liu and Yang Liu. 2023.
  Pluggable Neural Machine Translation Models via Memory-augmented Adapters.
  Preprint [arXiv]
• Sijie Cheng, Zhicheng Guo, Jingwen Wu, Kechen Fang, Peng Li, Huaping Liu and Yang Liu. 2023.
  Can Vision-Language Models Think from a First-Person Perspective?.
  Preprint [arXiv] [Project]

2022

• Chi Chen, Peng Li, Maosong Sun and 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 and 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 and 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 and 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 and 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 and 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]
• Yujia Qin, Xiaozhi Wang, Yusheng Su, Yankai Lin, Ning Ding, Jing Yi, Weize Chen, Zhiyuan Liu, Juanzi Li, Lei Hou, Peng Li, Maosong Sun and Jie Zhou. 2022.
  Exploring Universal Intrinsic Task Subspace via Prompt Tuning.
  Preprint [arXiv]
• Ryuichi Takanobu, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou and 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, and 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, and 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, and 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 and 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, and Maosong Sun. 2021.
  MOOCCubeX: A Large Knowledge-centered Repository for Adaptive Learning in MOOCs.
  In Proceedings of CIKM 2021, 4643-4652. [pdf] [code]
• Yusheng Su, Xu Han, Zhengyan Zhang, Peng Li, Zhiyuan Liu, Yankai Lin, Jie Zhou, and 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, 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. [pdf] [code]
• Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and 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, and 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, and 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, and 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, and 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, and 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, and 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*, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and Hao Zhou. 2020.
  WeChat Neural Machine Translation Systems for WMT20.
  In Proceedings of WMT20, 239–247. [pdf]
• 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. [pdf] [code]
• Xu Han, Yi Dai, Tianyu Gao, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, and 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, 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. [pdf]
• Feilong Chen, Fandong Meng, Jiaming Xu, Peng Li, Bo Xu, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and 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, and Xu Sun. 2019.
  HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Networks.
  Preprint [arXiv]
• Qiu Ran, Peng Li, Weiwei Hu, and Jie Zhou. 2019.
  Option Comparison Network for Multiple-choice Reading Comprehension.
  Preprint [arXiv] [code]

2008~2018

• Xu Han, Pengfei Yu, Zhiyuan Liu, Maosong Sun, and 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, and 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, and 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, and Dakun Zhang. 2014.
  A Neural Reordering Model for Phrase-based Translation.
  In Proceedings of COLING 2014, 1897-1907. [pdf] [slides]
• Peng Li, Yang Liu, and 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, and Maosong Sun. 2013.
  An Extended GHKM Algorithm for Inducing Lambda-SCFG.
  In Proceedings of AAAI-13, 605-611. [pdf] [slides]
• Peng Li, Yang Liu, and 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, and 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, and 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, and 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: COLING (2022), EACL (2024)
• PC Chair: YWCL (2010)
• Tutorial Chair: CCL (2023), CCMT (2023)
• Demonstration Chair: CCL (2024)
• Reviewer: NeurIPS (2022-2023), ICML (2022-2023), ICLR (2024), ACL (2014, 2021-2023), EMNLP (2014, 2021-2023), NAACL (2018), CVPR (2023-2024), ICCV (2023), AAAI (2022-2024), IJCAI (2022-2023), COLING (2020,2024), ACM TIST(2015), TACL (Standing Reviewer)

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: Dec 09, 2023.