default search action
Li Zhao 0007
Person information
- affiliation: Microsoft Research Asia, Beijing, China
- affiliation (PhD 2016): Tsinghua University, Beijing, China
Other persons with the same name
- Li Zhao — disambiguation page
- Li Zhao 0001
— Children's National Medical Center, Washington, DC, USA (and 2 more)
- Li Zhao 0002 — Intel Corporation, Hillsboro, OR, USA (and 1 more)
- Li Zhao 0003
- Li Zhao 0004
- Li Zhao 0005
- Li Zhao 0006 — Tsinghua University, Department of Computer Science and Technology, China
- Li Zhao 0008
- Li Zhao 0009
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [c42]Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim:
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) 2024: 8252-8271 - [c41]Qingpeng Cai
AgentIR: 1st Workshop on Agent-based Information Retrieval. SIGIR 2024: 3025-3028 - [i26]Guangran Cheng, Chuheng Zhang, Wenzhe Cai, Li Zhao, Changyin Sun, Jiang Bian:
Empowering Large Language Models on Robotic Manipulation with Affordance Prompting. CoRR abs/2404.11027 (2024) - [i25]Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang:
DPO Meets PPO: Reinforced Token Optimization for RLHF. CoRR abs/2404.18922 (2024) - [i24]Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian:
Video In-context Learning. CoRR abs/2407.07356 (2024) - [i23]Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim:
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR abs/2407.14733 (2024) - 2023
- [c40]Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian:
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. AAAI 2023: 8132-8140 - [c39]Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian:
H-TSP: Hierarchically Solving the Large-Scale Traveling Salesman Problem. AAAI 2023: 9345-9353 - [c38]Yuanying Cai, Chuheng Zhang, Hanye Zhao, Li Zhao, Jiang Bian:
Curriculum Offline Reinforcement Learning. AAMAS 2023: 1221-1229 - [c37]Xin Xin
DRL4IR: 4th Workshop on Deep Reinforcement Learning for Information Retrieval. CIKM 2023: 5304-5307 - [c36]Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian:
Robust Situational Reinforcement Learning in Face of Context Disturbances. ICML 2023: 41973-41989 - [c35]Chuheng Zhang, Yitong Duan, Xiaoyu Chen, Jianyu Chen, Jian Li, Li Zhao:
Towards Generalizable Reinforcement Learning for Trade Execution. IJCAI 2023: 4975-4983 - [c34]Yuchen Fang
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. KDD 2023: 4003-4012 - [c33]Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley Llorens:
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning. NeurIPS 2023 - [i22]Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian:
H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem. CoRR abs/2304.09395 (2023) - [i21]Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian:
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. CoRR abs/2304.09407 (2023) - [i20]Xiaoyu Chen, Shenao Zhang, Pushi Zhang, Li Zhao, Jianyu Chen:
Asking Before Action: Gather Information in Embodied Decision Making with Language Models. CoRR abs/2305.15695 (2023) - [i19]Xianliang Yang, Zhihao Liu, Wei Jiang
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management. CoRR abs/2306.07542 (2023) - [i18]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. CoRR abs/2307.03119 (2023) - [i17]Chuheng Zhang, Yitong Duan, Xiaoyu Chen, Jianyu Chen, Jian Li, Li Zhao:
Towards Generalizable Reinforcement Learning for Trade Execution. CoRR abs/2307.11685 (2023) - [i16]Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian:
Pre-Trained Large Language Models for Industrial Control. CoRR abs/2308.03028 (2023) - 2022
- [c32]Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu:
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoG 2022: 237-244 - [c31]Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. ICDM 2022: 21-30 - [c30]Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu:
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. ICLR 2022 - [c29]Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu:
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. NeurIPS 2022 - [c28]Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu:
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. NeurIPS 2022 - [c27]Xiangyu Zhao, Xin Xin
DRL4IR: 3rd Workshop on Deep Reinforcement Learning for Information Retrieval. SIGIR 2022: 3488-3491 - [i15]Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu:
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. CoRR abs/2202.06450 (2022) - [i14]Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu:
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. CoRR abs/2205.12418 (2022) - [i13]Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu:
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoRR abs/2207.08379 (2022) - [i12]Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. CoRR abs/2212.02125 (2022) - [i11]Yuandong Ding, Mingxiao Feng, Guozi Liu, Wei Jiang
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management. CoRR abs/2212.07684 (2022) - [i10]Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu:
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. CoRR abs/2212.12735 (2022) - 2021
- [j2]Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin
Demonstration actor critic. Neurocomputing 434: 194-202 (2021) - [c26]Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu:
Return-Based Contrastive Representation Learning for Reinforcement Learning. ICLR 2021 - [c25]Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu:
Independence-aware Advantage Estimation. IJCAI 2021: 3349-3355 - [c24]Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu:
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. NeurIPS 2021: 1519-1529 - [c23]Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu:
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. NeurIPS 2021: 3029-3042 - [c22]Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu:
Curriculum Offline Imitating Learning. NeurIPS 2021: 6266-6277 - [c21]Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang:
DRL4IR: 2nd Workshop on Deep Reinforcement Learning for Information Retrieval. SIGIR 2021: 2681-2684 - [i9]Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu:
Return-Based Contrastive Representation Learning for Reinforcement Learning. CoRR abs/2102.10960 (2021) - [i8]Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu:
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. CoRR abs/2110.13578 (2021) - [i7]Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu:
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. CoRR abs/2110.14118 (2021) - [i6]Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu:
Curriculum Offline Imitation Learning. CoRR abs/2111.02056 (2021) - 2020
- [c20]Zichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu:
RD$^2$: Reward Decomposition with Representation Decomposition. NeurIPS 2020 - [c19]Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu
Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs. SIGIR 2020: 239-248 - [c18]Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang, Alex Beutel:
Deep Reinforcement Learning for Information Retrieval: Fundamentals and Advances. SIGIR 2020: 2468-2471 - [i5]Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon:
Suphx: Mastering Mahjong with Deep Reinforcement Learning. CoRR abs/2003.13590 (2020)
2010 – 2019
- 2019
- [j1]Yijun Wang
Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 27(10): 1564-1576 (2019) - [c17]Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Trust Region Evolution Strategies. AAAI 2019: 4352-4359 - [c16]Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, Guangwen Yang:
Unified Policy Optimization for Robust Reinforcement Learning. ACML 2019: 395-410 - [c15]Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. KDD 2019: 894-902 - [c14]Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. KDD 2019: 2376-2384 - [c13]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. NeurIPS 2019: 6190-6199 - [c12]Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Tie-Yan Liu, Guangwen Yang:
Distributional Reward Decomposition for Reinforcement Learning. NeurIPS 2019: 6212-6221 - [i4]Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu:
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. CoRR abs/1911.02140 (2019) - [i3]Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu:
Distributional Reward Decomposition for Reinforcement Learning. CoRR abs/1911.02166 (2019) - 2018
- [c11]Yijun Wang
Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization. AAAI 2018: 5553-5560 - [c10]Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu:
Word Attention for Sequence to Sequence Text Understanding. AAAI 2018: 5578-5585 - [c9]Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu:
Reinforcement Learning for Relation Classification From Noisy Data. AAAI 2018: 5779-5786 - [c8]Tianyang Zhang, Minlie Huang, Li Zhao:
Learning Structured Representation for Text Classification via Reinforcement Learning. AAAI 2018: 6053-6060 - [c7]Lijun Wu, Yingce Xia, Fei Tian, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Adversarial Neural Machine Translation. ACML 2018: 534-549 - [c6]Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu:
Efficient Sequence Learning with Group Recurrent Networks. NAACL-HLT 2018: 799-808 - [i2]Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu:
Reinforcement Learning for Relation Classification from Noisy Data. CoRR abs/1808.08013 (2018) - 2017
- [c5]Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Sequence Prediction with Unlabeled Data by Reward Function Learning. IJCAI 2017: 3098-3104 - [i1]Lijun Wu, Yingce Xia, Li Zhao, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu:
Adversarial Neural Machine Translation. CoRR abs/1704.06933 (2017) - 2016
- [c4]Li Zhao, Minlie Huang, Ziyu Yao, Rongwei Su, Yingying Jiang, Xiaoyan Zhu:
Semi-Supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-Level Statistical Constraint. AAAI 2016: 2877-2884 - [c3]Yequan Wang, Minlie Huang, Xiaoyan Zhu, Li Zhao:
Attention-based LSTM for Aspect-level Sentiment Classification. EMNLP 2016: 606-615 - 2015
- [c2]Li Zhao, Minlie Huang, Jiashen Sun, Hengliang Luo, Xiankai Yang, Xiaoyan Zhu:
Sentiment Extraction by Leveraging Aspect-Opinion Association Structure. CIKM 2015: 343-352 - 2014
- [c1]Li Zhao, Minlie Huang, Haiqiang Chen, Junjun Cheng, Xiaoyan Zhu:
Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency. EMNLP 2014: 1614-1623
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-28 02:22 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: