Li Zhao

Principal Researcher

Publications

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- villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models
  
  Xiaoyu Chen, Hangxing Wei, Pushi Zhang, Chuheng Zhang, Kaixin Wang, Yanjiang Guo, Rushuai Yang, Yucen Wang, Xinquan Xiao, Li Zhao, Jianyu Chen, Jiang Bian
  
  ICLR 2026 | July 2025
  
  Publication
- Dyn-O: Building Structured World Models with Object-Centric Representations
  
  Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian
  
  NeurIPS 2025 | July 2025
  
  DOI
- What Do Latent Action Models Actually Learn?
  
  Chuheng Zhang, Tim Pearce, Pushi Zhang, Kaixin Wang, Xiaoyu Chen, Wei Shen, Li Zhao, Jiang Bian
  
  NeurIPS 2025 | May 2025
  
  DOI Publication Publication
- AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
  
  Yuliang Liu, Junjie Lu, Zhaoling Chen, Chaofeng Qu, Jason Klein Liu, Chonghan Liu, Zefan Cai, Yunhui Xia, Li Zhao, Jiang Bian, Chuheng Zhang, Wei Shen, Zhouhan Lin
  
  ICML 2025 | February 2025
  
  DOI
- IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
  
  Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian
  
  October 2024
  
  Publication PDF Project
- Policy Filtration for RLHF to Mitigate Noise in Reward Models
  
  Chuheng Zhang, Wei Shen, Li Zhao, Xuyun Zhang, Xiaolong Xu, Wanchun Dou, Jiang Bian
  
  ICML 2025 | September 2024
  
  Publication
- Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
  
  Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
  
  IJCAI 2024 | July 2024
  
  DOI
- Video In-context Learning
  
  Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
  
  July 2024
  
  Publication Project
- DPO Meets PPO: Reinforced Token Optimization for RLHF
  
  Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
  
  ICML 2025 | April 2024
  
  DOI Publication Publication
- Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
  
  Xinqiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
  
  2023 Neural Information Processing Systems | December 2023
  
  Publication Publication
- Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
  
  Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
  
  NeurIPS 2023 | September 2023
  
  Publication
- Robust Situational Reinforcement Learning in Face of Context Disturbances
  
  Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
  
  Proceedings of the 40th International Conference on Machine Learning (ICML) | September 2023
  
  Publication
- Pre-Trained Large Language Models for Industrial Control
  
  Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
  
  ArXiv | August 2023, Vol abs/2308.03028
  
  DOI Publication Publication Video
- Asking Before Action: Gather Information in Embodied Decision Making with Language Models
  
  Xiaoyu Chen, Shenao Zhang, Pushi Zhang, Li Zhao, Jianyu Chen
  
  Arxiv Preprint | May 2023
  
  Publication
- TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
  
  Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tie-Yan Liu
  
  IEEE International Conference on Data Mining (Best Student Paper Runner-Up Awards) | January 2023
  
  Publication
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
  Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
  
  Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | October 2022
  
  Publication
- Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
  
  Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
  
  Tenth International Conference on Learning Representations(ICLR) | April 2022
  
  Publication
- Curriculum Offline Imitating Learning
  
  Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
  
  Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
  
  Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Return-Based Contrastive Representation Learning for Reinforcement Learning
  
  Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu
  
  Ninth International Conference on Learning Representations(ICLR) | January 2021
  
  Publication Project
- RD2: Reward Decomposition with Representation Disentanglement
  
  Zichuan Lin, Derek Yang, Li Zhao, Tao Qin (taoqin), Guangwen Yang, Tie-Yan Liu
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2020
  
  Publication Project
- Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs
  
  Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu, Chunxiao Xing, Xing Xie
  
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | June 2020
  
  PDF DOI
- Distributional Reward Decomposition for Reinforcement Learning
  
  Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu
  
  Proceedings of the 33th Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Publication Project
- Fully Parameterized Quantile Function for Distributional Reinforcement Learning
  
  Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu
  
  Proceedings of the 33th Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Publication Project
- Demonstration Actor Critic
  
  Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
  
  November 2019
  
  Publication Project
- Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
  
  Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
  
  25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019
  
  Publication Project
- Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction
  
  Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
  
  25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019
  
  Publication Project
- Trust Region Evolution Strategies
  
  Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
  
  Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence | February 2019
  
  Publication Project
- Efficient Sequence Learning with Group Recurrent Networks
  
  Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
  
  NAACL | November 2018
  
  Publication
- Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization
  
  Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, GuiQuan liu, Tie-Yan Liu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Learning Structured Representation for Text Classification via Reinforcement Learning
  
  Tianyang Zhang, Minlie Huang, Li Zhao
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Reinforcement Learning for Relation Classification from Noisy Data
  
  Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Word Attention for Sequence to Sequence Text Understanding
  
  Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Sequence Prediction with Unlabeled Data by Reward Function Learning
  
  Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu
  
  Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence | August 2017
  
  Publication
- Attention-based LSTM for Aspect-level Sentiment Classification
  
  Yequan Wang, Minlie Huang, Li Zhao (lizo), Xiaoyan Zhu
  
  Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing | November 2016
  
  Publication
- Semi-supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-level Statistical Constraint
  
  Li Zhao, Minlie Huang, Ziyu Yao, Rongwei Su, Yingying Jiang, Xiaoyan
  
  Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence | February 2016
  
  Publication
- Sentiment Extraction by Leveraging Aspect-Opinion Association Structure
  
  Li Zhao, Minlie Huang, Jiashen Sun, Hengliang Luo, Xiankai Yang, Xiaoyan Zhu
  
  Proceedings of the 24th ACM International Conference on Information and Knowledge Management | October 2015
  
  Publication
- Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency
  
  Li Zhao, Minlie Huang, Xiaoyan Zhu
  
  EMNLP 2014 - Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing | October 2014
  
  Publication

- villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models
  
  Xiaoyu Chen, Hangxing Wei, Pushi Zhang, Chuheng Zhang, Kaixin Wang, Yanjiang Guo, Rushuai Yang, Yucen Wang, Xinquan Xiao, Li Zhao, Jianyu Chen, Jiang Bian
  
  ICLR 2026 | July 2025
  
  Publication
- Dyn-O: Building Structured World Models with Object-Centric Representations
  
  Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian
  
  NeurIPS 2025 | July 2025
  
  DOI
- What Do Latent Action Models Actually Learn?
  
  Chuheng Zhang, Tim Pearce, Pushi Zhang, Kaixin Wang, Xiaoyu Chen, Wei Shen, Li Zhao, Jiang Bian
  
  NeurIPS 2025 | May 2025
  
  DOI Publication Publication
- AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
  
  Yuliang Liu, Junjie Lu, Zhaoling Chen, Chaofeng Qu, Jason Klein Liu, Chonghan Liu, Zefan Cai, Yunhui Xia, Li Zhao, Jiang Bian, Chuheng Zhang, Wei Shen, Zhouhan Lin
  
  ICML 2025 | February 2025
  
  DOI
- IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
  
  Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian
  
  October 2024
  
  Publication PDF Project
- Policy Filtration for RLHF to Mitigate Noise in Reward Models
  
  Chuheng Zhang, Wei Shen, Li Zhao, Xuyun Zhang, Xiaolong Xu, Wanchun Dou, Jiang Bian
  
  ICML 2025 | September 2024
  
  Publication
- Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
  
  Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
  
  IJCAI 2024 | July 2024
  
  DOI
- DPO Meets PPO: Reinforced Token Optimization for RLHF
  
  Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
  
  ICML 2025 | April 2024
  
  DOI Publication Publication
- Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
  
  Xinqiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
  
  2023 Neural Information Processing Systems | December 2023
  
  Publication Publication
- Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
  
  Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
  
  NeurIPS 2023 | September 2023
  
  Publication
- Robust Situational Reinforcement Learning in Face of Context Disturbances
  
  Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
  
  Proceedings of the 40th International Conference on Machine Learning (ICML) | September 2023
  
  Publication
- Pre-Trained Large Language Models for Industrial Control
  
  Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
  
  ArXiv | August 2023, Vol abs/2308.03028
  
  DOI Publication Publication Video
- Asking Before Action: Gather Information in Embodied Decision Making with Language Models
  
  Xiaoyu Chen, Shenao Zhang, Pushi Zhang, Li Zhao, Jianyu Chen
  
  Arxiv Preprint | May 2023
  
  Publication
- TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
  
  Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tie-Yan Liu
  
  IEEE International Conference on Data Mining (Best Student Paper Runner-Up Awards) | January 2023
  
  Publication
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
  Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
  
  Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | October 2022
  
  Publication
- Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
  
  Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
  
  Tenth International Conference on Learning Representations(ICLR) | April 2022
  
  Publication
- Curriculum Offline Imitating Learning
  
  Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
  
  Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
  
  Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Return-Based Contrastive Representation Learning for Reinforcement Learning
  
  Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu
  
  Ninth International Conference on Learning Representations(ICLR) | January 2021
  
  Publication Project
- RD2: Reward Decomposition with Representation Disentanglement
  
  Zichuan Lin, Derek Yang, Li Zhao, Tao Qin (taoqin), Guangwen Yang, Tie-Yan Liu
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2020
  
  Publication Project
- Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs
  
  Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu, Chunxiao Xing, Xing Xie
  
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | June 2020
  
  PDF DOI
- Fully Parameterized Quantile Function for Distributional Reinforcement Learning
  
  Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu
  
  Proceedings of the 33th Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Publication Project
- Distributional Reward Decomposition for Reinforcement Learning
  
  Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu
  
  Proceedings of the 33th Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Publication Project
- Demonstration Actor Critic
  
  Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
  
  November 2019
  
  Publication Project
- Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
  
  Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
  
  25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019
  
  Publication Project
- Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction
  
  Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
  
  25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019
  
  Publication Project
- Trust Region Evolution Strategies
  
  Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
  
  Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence | February 2019
  
  Publication Project
- Efficient Sequence Learning with Group Recurrent Networks
  
  Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
  
  NAACL | November 2018
  
  Publication
- Reinforcement Learning for Relation Classification from Noisy Data
  
  Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Word Attention for Sequence to Sequence Text Understanding
  
  Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization
  
  Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, GuiQuan liu, Tie-Yan Liu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Learning Structured Representation for Text Classification via Reinforcement Learning
  
  Tianyang Zhang, Minlie Huang, Li Zhao
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Sequence Prediction with Unlabeled Data by Reward Function Learning
  
  Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu
  
  Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence | August 2017
  
  Publication
- Attention-based LSTM for Aspect-level Sentiment Classification
  
  Yequan Wang, Minlie Huang, Li Zhao (lizo), Xiaoyan Zhu
  
  Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing | November 2016
  
  Publication
- Semi-supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-level Statistical Constraint
  
  Li Zhao, Minlie Huang, Ziyu Yao, Rongwei Su, Yingying Jiang, Xiaoyan
  
  Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence | February 2016
  
  Publication
- Sentiment Extraction by Leveraging Aspect-Opinion Association Structure
  
  Li Zhao, Minlie Huang, Jiashen Sun, Hengliang Luo, Xiankai Yang, Xiaoyan Zhu
  
  Proceedings of the 24th ACM International Conference on Information and Knowledge Management | October 2015
  
  Publication
- Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency
  
  Li Zhao, Minlie Huang, Xiaoyan Zhu
  
  EMNLP 2014 - Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing | October 2014
  
  Publication
- Video In-context Learning
  
  Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
  
  July 2024
  
  Publication Project
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
  Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency
  
  Li Zhao, Minlie Huang, Xiaoyan Zhu
  
  EMNLP 2014 - Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing | October 2014
  
  Publication

- villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models
  
  Xiaoyu Chen, Hangxing Wei, Pushi Zhang, Chuheng Zhang, Kaixin Wang, Yanjiang Guo, Rushuai Yang, Yucen Wang, Xinquan Xiao, Li Zhao, Jianyu Chen, Jiang Bian
  
  ICLR 2026 | July 2025
  
  Publication
- Dyn-O: Building Structured World Models with Object-Centric Representations
  
  Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian
  
  NeurIPS 2025 | July 2025
  
  DOI
- What Do Latent Action Models Actually Learn?
  
  Chuheng Zhang, Tim Pearce, Pushi Zhang, Kaixin Wang, Xiaoyu Chen, Wei Shen, Li Zhao, Jiang Bian
  
  NeurIPS 2025 | May 2025
  
  DOI Publication Publication
- AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
  
  Yuliang Liu, Junjie Lu, Zhaoling Chen, Chaofeng Qu, Jason Klein Liu, Chonghan Liu, Zefan Cai, Yunhui Xia, Li Zhao, Jiang Bian, Chuheng Zhang, Wei Shen, Zhouhan Lin
  
  ICML 2025 | February 2025
  
  DOI
- IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
  
  Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian
  
  October 2024
  
  Publication PDF Project
- Policy Filtration for RLHF to Mitigate Noise in Reward Models
  
  Chuheng Zhang, Wei Shen, Li Zhao, Xuyun Zhang, Xiaolong Xu, Wanchun Dou, Jiang Bian
  
  ICML 2025 | September 2024
  
  Publication
- Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
  
  Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
  
  IJCAI 2024 | July 2024
  
  DOI
- DPO Meets PPO: Reinforced Token Optimization for RLHF
  
  Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
  
  ICML 2025 | April 2024
  
  DOI Publication Publication
- Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
  
  Xinqiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
  
  2023 Neural Information Processing Systems | December 2023
  
  Publication Publication
- Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
  
  Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
  
  NeurIPS 2023 | September 2023
  
  Publication
- Robust Situational Reinforcement Learning in Face of Context Disturbances
  
  Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
  
  Proceedings of the 40th International Conference on Machine Learning (ICML) | September 2023
  
  Publication
- Asking Before Action: Gather Information in Embodied Decision Making with Language Models
  
  Xiaoyu Chen, Shenao Zhang, Pushi Zhang, Li Zhao, Jianyu Chen
  
  Arxiv Preprint | May 2023
  
  Publication
- TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
  
  Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tie-Yan Liu
  
  IEEE International Conference on Data Mining (Best Student Paper Runner-Up Awards) | January 2023
  
  Publication
- Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
  
  Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | November 2022
  
  PDF
- An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
  
  Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu
  
  Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) | October 2022
  
  Publication
- Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
  
  Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
  
  Tenth International Conference on Learning Representations(ICLR) | April 2022
  
  Publication
- Curriculum Offline Imitating Learning
  
  Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
  
  Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
  
  Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu
  
  Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS) | December 2021
  
  Publication Project
- Return-Based Contrastive Representation Learning for Reinforcement Learning
  
  Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu
  
  Ninth International Conference on Learning Representations(ICLR) | January 2021
  
  Publication Project
- RD2: Reward Decomposition with Representation Disentanglement
  
  Zichuan Lin, Derek Yang, Li Zhao, Tao Qin (taoqin), Guangwen Yang, Tie-Yan Liu
  
  Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS) | December 2020
  
  Publication Project
- Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs
  
  Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu, Chunxiao Xing, Xing Xie
  
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | June 2020
  
  PDF DOI
- Fully Parameterized Quantile Function for Distributional Reinforcement Learning
  
  Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu
  
  Proceedings of the 33th Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Publication Project
- Distributional Reward Decomposition for Reinforcement Learning
  
  Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu
  
  Proceedings of the 33th Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Publication Project
- Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
  
  Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
  
  25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019
  
  Publication Project
- Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction
  
  Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
  
  25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019
  
  Publication Project
- Trust Region Evolution Strategies
  
  Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
  
  Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence | February 2019
  
  Publication Project
- Efficient Sequence Learning with Group Recurrent Networks
  
  Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
  
  NAACL | November 2018
  
  Publication
- Reinforcement Learning for Relation Classification from Noisy Data
  
  Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Word Attention for Sequence to Sequence Text Understanding
  
  Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization
  
  Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, GuiQuan liu, Tie-Yan Liu
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Learning Structured Representation for Text Classification via Reinforcement Learning
  
  Tianyang Zhang, Minlie Huang, Li Zhao
  
  Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence | February 2018
  
  Publication
- Sequence Prediction with Unlabeled Data by Reward Function Learning
  
  Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu
  
  Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence | August 2017
  
  Publication
- Attention-based LSTM for Aspect-level Sentiment Classification
  
  Yequan Wang, Minlie Huang, Li Zhao (lizo), Xiaoyan Zhu
  
  Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing | November 2016
  
  Publication
- Semi-supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-level Statistical Constraint
  
  Li Zhao, Minlie Huang, Ziyu Yao, Rongwei Su, Yingying Jiang, Xiaoyan
  
  Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence | February 2016
  
  Publication
- Sentiment Extraction by Leveraging Aspect-Opinion Association Structure
  
  Li Zhao, Minlie Huang, Jiashen Sun, Hengliang Luo, Xiankai Yang, Xiaoyan Zhu
  
  Proceedings of the 24th ACM International Conference on Information and Knowledge Management | October 2015
  
  Publication
- Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency
  
  Li Zhao, Minlie Huang, Xiaoyan Zhu
  
  EMNLP 2014 - Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing | October 2014
  
  Publication
- Video In-context Learning
  
  Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
  
  July 2024
  
  Publication Project
- Pre-Trained Large Language Models for Industrial Control
  
  Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
  
  ArXiv | August 2023, Vol abs/2308.03028
  
  DOI Publication Publication Video
- Demonstration Actor Critic
  
  Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
  
  November 2019
  
  Publication Project

Li Zhao

Publications

villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models

Dyn-O: Building Structured World Models with Object-Centric Representations

What Do Latent Action Models Actually Learn?

AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence

IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI

Policy Filtration for RLHF to Mitigate Noise in Reward Models

Diversification of Adaptive Policy for Effective Offline Reinforcement Learning

Video In-context Learning

DPO Meets PPO: Reinforced Token Optimization for RLHF

Distributional Pareto-Optimal Multi-Objective Reinforcement Learning

Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution

Robust Situational Reinforcement Learning in Face of Context Disturbances

Pre-Trained Large Language Models for Industrial Control

Asking Before Action: Gather Information in Embodied Decision Making with Language Models

TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret

An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context

Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality

Curriculum Offline Imitating Learning

Distributional Reinforcement Learning for Multi-Dimensional Reward Functions

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning

Return-Based Contrastive Representation Learning for Reinforcement Learning

RD2: Reward Decomposition with Representation Disentanglement

Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs

Distributional Reward Decomposition for Reinforcement Learning

Fully Parameterized Quantile Function for Distributional Reinforcement Learning

Demonstration Actor Critic

Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

Trust Region Evolution Strategies

Efficient Sequence Learning with Group Recurrent Networks

Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization

Learning Structured Representation for Text Classification via Reinforcement Learning

Reinforcement Learning for Relation Classification from Noisy Data

Word Attention for Sequence to Sequence Text Understanding

Sequence Prediction with Unlabeled Data by Reward Function Learning

Attention-based LSTM for Aspect-level Sentiment Classification

Semi-supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-level Statistical Constraint

Sentiment Extraction by Leveraging Aspect-Opinion Association Structure

Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency

villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models

Dyn-O: Building Structured World Models with Object-Centric Representations

What Do Latent Action Models Actually Learn?

AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence

IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI

Policy Filtration for RLHF to Mitigate Noise in Reward Models

Diversification of Adaptive Policy for Effective Offline Reinforcement Learning

DPO Meets PPO: Reinforced Token Optimization for RLHF

Distributional Pareto-Optimal Multi-Objective Reinforcement Learning

Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution

Robust Situational Reinforcement Learning in Face of Context Disturbances

Pre-Trained Large Language Models for Industrial Control

Asking Before Action: Gather Information in Embodied Decision Making with Language Models

TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret

An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context

Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality

Curriculum Offline Imitating Learning

Distributional Reinforcement Learning for Multi-Dimensional Reward Functions

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning

Return-Based Contrastive Representation Learning for Reinforcement Learning

RD2: Reward Decomposition with Representation Disentanglement

Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs

Fully Parameterized Quantile Function for Distributional Reinforcement Learning

Distributional Reward Decomposition for Reinforcement Learning

Demonstration Actor Critic

Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

Trust Region Evolution Strategies

Efficient Sequence Learning with Group Recurrent Networks

Reinforcement Learning for Relation Classification from Noisy Data

Word Attention for Sequence to Sequence Text Understanding

Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization

Learning Structured Representation for Text Classification via Reinforcement Learning

Sequence Prediction with Unlabeled Data by Reward Function Learning

Attention-based LSTM for Aspect-level Sentiment Classification

Semi-supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-level Statistical Constraint

Sentiment Extraction by Leveraging Aspect-Opinion Association Structure