Li, Chenliang

25 publications

IJCAI 2025 Flow Matching Based Sequential Recommender Model Feng Liu, Lixin Zou, Xiangyu Zhao, Min Tang, Liming Dong, Dan Luo, Xiangyang Luo, Chenliang Li

ICLR 2025 Joint Reward and Policy Learning with Demonstrations and Human Feedback Improves Alignment Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo Garcia, Mingyi Hong

ICLRW 2025 Reinforcement Learning in Inference Time: A Perspective from Successive Policy Iterations Xinnan Zhang, Chenliang Li, Siliang Zeng, Jiaxiang Li, Zhongruo Wang, Songtao Lu, Alfredo Garcia, Mingyi Hong

AISTATS 2025 Understanding Inverse Reinforcement Learning Under Overparameterization: Non-Asymptotic Analysis and Global Optimality Ruijia Zhang, Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPS 2025 WritingBench: A Comprehensive Benchmark for Generative Writing Yuning Wu, Jiahao Mei, Ming Yan, Chenliang Li, Shaopeng Lai, Yuran Ren, Wang Zijia, Ji Zhang, Mengyue Wu, Qin Jin, Fei Huang

AAAI 2024 Dependency Structure-Enhanced Graph Attention Networks for Event Detection Qizhi Wan, Changxuan Wan, Keli Xiao, Kun Lu, Chenliang Li, Xiping Liu, Dexi Liu

NeurIPS 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo Garcia, Mingyi Hong

ICMLW 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment Jiaxiang Li, Siliang Zeng, Hoi To Wai, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPSW 2024 Learning Reward and Policy Jointly from Demonstration and Preference Improves Alignment Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo Garcia, Mingyi Hong

CoRL 2023 A Bayesian Approach to Robust Inverse Reinforcement Learning Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony D McDonald, Mingyi Hong

ICCV 2023 BUS: Efficient and Effective Vision-Language Pre-Training with Bottom-up Patch Summarization. Chaoya Jiang, Haiyang Xu, Wei Ye, Qinghao Ye, Chenliang Li, Ming Yan, Bin Bi, Shikun Zhang, Fei Huang, Songfang Huang

ICCV 2023 Learning Trajectory-Word Alignments for Video-Language Tasks Xu Yang, Zhangzikang Li, Haiyang Xu, Hanwang Zhang, Qinghao Ye, Chenliang Li, Ming Yan, Yu Zhang, Fei Huang, Songfang Huang

ICMLW 2023 Robust Inverse Reinforcement Learning Through Bayesian Theory of Mind Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony McDonald, Mingyi Hong

NeurIPS 2023 When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

ICML 2023 mPLUG-2: A Modularized Multi-Modal Foundation Model Across Text, Image and Video Haiyang Xu, Qinghao Ye, Ming Yan, Yaya Shi, Jiabo Ye, Yuanhong Xu, Chenliang Li, Bin Bi, Qi Qian, Wei Wang, Guohai Xu, Ji Zhang, Songfang Huang, Fei Huang, Jingren Zhou

IJCAI 2022 Global Inference with Explicit Syntactic and Discourse Structures for Dialogue-Level Relation Extraction Hao Fei, Jingye Li, Shengqiong Wu, Chenliang Li, Donghong Ji, Fei Li

IJCAI 2022 Inheriting the Wisdom of Predecessors: A Multiplex Cascade Framework for Unified Aspect-Based Sentiment Analysis Hao Fei, Fei Li, Chenliang Li, Shengqiong Wu, Jingye Li, Donghong Ji

NeurIPS 2022 Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

ICMLW 2022 Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

AAAI 2021 A Unified Pretraining Framework for Passage Ranking and Expansion Ming Yan, Chenliang Li, Bin Bi, Wei Wang, Songfang Huang

IJCAI 2021 Pattern-Enhanced Contrastive Policy Learning Network for Sequential Recommendation Xiaohai Tong, Pengfei Wang, Chenliang Li, Long Xia, Shaozhang Niu

AAAI 2020 CASE: Context-Aware Semantic Expansion Jialong Han, Aixin Sun, Haisong Zhang, Chenliang Li, Shuming Shi

AAAI 2020 Generating Well-Formed Answers by Machine Reading with Stochastic Selector Networks Bin Bi, Chen Wu, Ming Yan, Wei Wang, Jiangnan Xia, Chenliang Li

IJCAI 2019 A Review-Driven Neural Model for Sequential Recommendation Chenliang Li, Xichuan Niu, Xiangyang Luo, Zhenzhong Chen, Cong Quan

AAAI 2019 Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding Peifeng Wang, Jialong Han, Chenliang Li, Rong Pan