Dyn-O: Building Structured World Models with Object-Centric Representations
Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian
NeurIPS 2025 | July 2025
Li Zhao
Principal Researcher
出版物
-
-
-
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
-
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
-
-
-
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
-
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
-
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
-
Video In-context Learning
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
July 2024
-
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
-
-
-
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
-
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
-
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
-
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
ArXiv | August 2023, 巻abs/2308.03028
-
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
-
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
-
-
-
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
-
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
-
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
-
-
-
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
-
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
-
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
-
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
-
-
-
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
-
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
-
-
-
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
-
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
-
Demonstration Actor Critic
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
November 2019
-
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
-
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
-
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
-
-
-
Efficient Sequence Learning with Group Recurrent Networks
Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
NAACL | November 2018
-
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
-
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
-
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
-
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
-
-
-
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
-
-
-
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
-
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
-
-
-
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
-
-
-
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
-
-
-
Dyn-O: Building Structured World Models with Object-Centric Representations
Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian
NeurIPS 2025 | July 2025
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
ArXiv | August 2023, 巻abs/2308.03028
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
Demonstration Actor Critic
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
November 2019
-
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
-
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
-
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
-
Efficient Sequence Learning with Group Recurrent Networks
Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
NAACL | November 2018
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
-
-
Video In-context Learning
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
July 2024
-
-
-
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
-
-
-
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
-
-
-
Dyn-O: Building Structured World Models with Object-Centric Representations
Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian
NeurIPS 2025 | July 2025
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
Efficient Sequence Learning with Group Recurrent Networks
Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
NAACL | November 2018
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
-
-
Video In-context Learning
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
July 2024
-
-
-
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
ArXiv | August 2023, 巻abs/2308.03028
-
-
-
Demonstration Actor Critic
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
November 2019
-