Baoxiang Wang - RankMe

98 papers A* 28A 11Misc 1Journal 55Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning. CoRR Dan Qiao, Binbin Chen, Fengyu Cai, Jianlong Chen, Wenhao Li, Fuxin Jiang, Zuzhi Chen, Hongyuan Zha, Tieying Zhang, Baoxiang Wang
2026	J	`jnl`	Talk, Judge, Cooperate: Gossip-Driven Indirect Reciprocity in Self-Interested LLM Agents. CoRR Shuhui Zhu, Yue Lin, Shriya Kaistha, Wenhao Li, Baoxiang Wang, Hongyuan Zha, Gillian K. Hadfield, Pascal Poupart
2026	J	`jnl`	The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL. CoRR Yingru Li, Jiawei Xu, Ziniu Li, Jiacai Liu, Wei Liu, Yuxuan Tong, Longtao Zheng, Zhenghai Xue, Yaxiang Zhang, Tianle Cai, Ge Zhang, Qian Liu, Baoxiang Wang
2025	A*	`conf`	A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD. ICML Ruinan Jin, Xiao Li, Yaoliang Yu, Baoxiang Wang
2025	J	`jnl`	ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning. CoRR Zeyuan Liu, Zhihe Yang, Jiawei Xu, Rui Yang, Jiafei Lyu, Baoxiang Wang, Yunjian Xu, Xiu Li
2025	A*	`conf`	Improved Approximation Algorithms for k-Submodular Maximization via Multilinear Extension. ICLR Huanjian Zhou, Lingxiao Huang, Baoxiang Wang
2025	J	`jnl`	Information Bargaining: Bilateral Commitment in Bayesian Persuasion. CoRR Yue Lin, Shuhui Zhu, William A. Cunningham, Wenhao Li, Pascal Poupart, Hongyuan Zha, Baoxiang Wang
2025	A*	`conf`	Last-iterate Convergence in Regularized Graphon Mean Field Game. AAAI Jing Dong, Baoxiang Wang, Yaoliang Yu
2025	A*	`conf`	Learning Imperfect Information Extensive-form Games with Last-iterate Convergence under Bandit Feedback. ICML Canzhe Zhao, Yutian Cheng, Jing Dong, Baoxiang Wang, Shuai Li
2025	A*	`conf`	Learning to Communicate Through Implicit Communication Channels. ICLR Han Wang, Binbin Chen, Tieying Zhang, Baoxiang Wang
2025	A	`conf`	Learning to Negotiate via Voluntary Commitment. AISTATS Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
2025	J	`jnl`	Learning to Negotiate via Voluntary Commitment. CoRR Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
2025	A*	`conf`	Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions. AAAI Canzhe Zhao, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
2025	A	`conf`	Multi-Agent Credit Assignment with Pretrained Language Models. AISTATS Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Wei Yin, Hao Shen, Bo Jin, Hongyuan Zha
2025	J	`jnl`	Offline Multi-agent Reinforcement Learning via Score Decomposition. CoRR Dan Qiao, Wenhao Li, Shanchao Yang, Hongyuan Zha, Baoxiang Wang
2025	J	`jnl`	Pointwise Convergence in Games with Conflicting Interest. CoRR Nanxiang Zhou, Jing Dong, Baoxiang Wang
2025	J	`jnl`	Policy-Conditioned Policies for Multi-Agent Task Solving. CoRR Yue Lin, Shuhui Zhu, Wenhao Li, Ang Li, Dan Qiao, Pascal Poupart, Hongyuan Zha, Baoxiang Wang
2025	J	`jnl`	Reinforcement Learning for Target Zone Blood Glucose Control. CoRR David H. Mguni, Jing Dong, Wanrong Yang, Ziquan Liu, Muhammad Salman Haleem, Baoxiang Wang
2025	A*	`conf`	Reward Translation via Reward Machine in Semi-Alignable MDPs. ICML Yun Hua, Haosheng Chen, Wenhao Li, Bo Jin, Baoxiang Wang, Hongyuan Zha, Xiangfeng Wang
2025	A*	`conf`	Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling. ICLR Jiawei Xu, Rui Yang, Shuang Qiu, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han
2025	J	`jnl`	Taming the Tail: Stable LLM Reinforcement Learning via Dynamic Vocabulary Pruning. CoRR Yingru Li, Jiawei Xu, Jiacai Liu, Yuxuan Tong, Ziniu Li, Tianle Cai, Ge Zhang, Qian Liu, Baoxiang Wang
2025	A*	`conf`	The adaptive complexity of parallelized log-concave sampling. ICLR Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
2025	J	`jnl`	Trust Region Masking for Long-Horizon LLM Reinforcement Learning. CoRR Yingru Li, Jiacai Liu, Jiawei Xu, Yuxuan Tong, Ziniu Li, Baoxiang Wang
2025	J	`jnl`	Verbalized Bayesian Persuasion. CoRR Wenhao Li, Yue Lin, Xiangfeng Wang, Bo Jin, Hongyuan Zha, Baoxiang Wang
2024	J	`jnl`	A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD. CoRR Ruinan Jin, Xiao Li, Yaoliang Yu, Baoxiang Wang
2024	J	`jnl`	Adaptive complexity of log-concave sampling. CoRR Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
2024	J	`jnl`	Asymptotic and Non-Asymptotic Convergence Analysis of AdaGrad for Non-Convex Optimization via Novel Stopping Time-based Analysis. CoRR Ruinan Jin, Xiaoyu Wang, Baoxiang Wang
2024	A*	`conf`	Carbon Market Simulation with Adaptive Mechanism Design. IJCAI Han Wang, Wenhao Li, Hongyuan Zha, Baoxiang Wang
2024	J	`jnl`	Carbon Market Simulation with Adaptive Mechanism Design. CoRR Han Wang, Wenhao Li, Hongyuan Zha, Baoxiang Wang
2024	—	`conf`	Convergence to Equilibrium of No-Regret Dynamics in Congestion Games. WINE Volkan Cevher, Wei Chen, Leello Dadi, Jing Dong, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Baoxiang Wang, Siwei Wang, Jingyu Wu
2024	A	`conf`	Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games. AISTATS Jing Dong, Baoxiang Wang, Yaoliang Yu
2024	J	`jnl`	Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games. CoRR Jing Dong, Baoxiang Wang, Yaoliang Yu
2024	A*	`conf`	Few-Shot Diffusion Models Escape the Curse of Dimensionality. NeurIPS Ruofeng Yang, Bo Jiang, Cheng Chen, Ruinan Jin, Baoxiang Wang, Shuai Li
2024	J	`jnl`	Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. Trans. Mach. Learn. Res. Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
2024	J	`jnl`	Last-iterate Convergence in Regularized Graphon Mean Field Game. CoRR Jing Dong, Baoxiang Wang, Yaoliang Yu
2024	J	`jnl`	Learning Fair Representations via Distance Correlation Minimization. IEEE Trans. Neural Networks Learn. Syst. Dandan Guo, Chaojie Wang, Baoxiang Wang, Hongyuan Zha
2024	J	`jnl`	Learning to Construct Implicit Communication Channel. CoRR Han Wang, Binbin Chen, Tieying Zhang, Baoxiang Wang
2024	A*	`conf`	On Stationary Point Convergence of PPO-Clip. ICLR Ruinan Jin, Shuai Li, Baoxiang Wang
2024	J	`jnl`	On the Decomposition of Differential Game. CoRR Nanxiang Zhou, Jing Dong, Yutian Li, Baoxiang Wang
2024	A*	`conf`	Online Control with Adversarial Disturbance for Continuous-time Linear Systems. NeurIPS Jingwei Li, Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang
2024	A	`conf`	Online Policy Optimization for Robust Markov Decision Process. UAI Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
2024	A*	`conf`	Relative Policy-Transition Optimization for Fast Policy Transfer. AAAI Jiawei Xu, Cheng Zhou, Yizheng Zhang, Baoxiang Wang, Lei Han
2024	J	`jnl`	Robust Decision Transformer: Tackling Data Corruption in Offline RL via Sequence Modeling. CoRR Jiawei Xu, Rui Yang, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han
2024	J	`jnl`	Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback. CoRR Jing Dong, Baoxiang Wang, Yaoliang Yu
2023	A*	`conf`	DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. IJCAI Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
2023	J	`jnl`	DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. CoRR Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
2023	A	`conf`	Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. WSDM Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
2023	A	`conf`	Diverse Policy Optimization for Structured Action Space. AAMAS Wenhao Li, Baoxiang Wang, Shanchao Yang, Hongyuan Zha
2023	J	`jnl`	Diverse Policy Optimization for Structured Action Space. CoRR Wenhao Li, Baoxiang Wang, Shanchao Yang, Hongyuan Zha
2023	J	`jnl`	Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. CoRR Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
2023	A*	`conf`	Information Design in Multi-Agent Reinforcement Learning. NeurIPS Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang
2023	J	`jnl`	Information Design in Multi-Agent Reinforcement Learning. CoRR Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang
2023	A*	`conf`	Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition. ICLR Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Shuai Li
2023	A*	`conf`	Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. NeurIPS Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li
2023	J	`jnl`	Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. CoRR Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li
2023	A*	`conf`	Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning. AAAI Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang
2023	J	`jnl`	Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring. Trans. Mach. Learn. Res. Shanchao Yang, Kaili Ma, Baoxiang Wang, Tianshu Yu, Hongyuan Zha
2023	J	`jnl`	Online Control with Adversarial Disturbance for Continuous-time Linear Systems. CoRR Jingwei Li, Jing Dong, Baoxiang Wang, Jingzhao Zhang
2023	A	`conf`	Online Influence Maximization under Decreasing Cascade Model. AAMAS Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
2023	J	`jnl`	Online Influence Maximization under Decreasing Cascade Model. CoRR Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
2023	A	`conf`	Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation. AAMAS Jing Dong, Li Shen, Yinggan Xu, Baoxiang Wang
2023	J	`jnl`	Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning. CoRR Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Bo Jin, Hongyuan Zha
2023	J	`jnl`	Taming the Exponential Action Set: Sublinear Regret and Fast Convergence to Nash Equilibrium in Online Congestion Games. CoRR Jing Dong, Jingyu Wu, Siwei Wang, Baoxiang Wang, Wei Chen
2023	A*	`conf`	Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning. NeurIPS Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Fei Wu, Jun Xiao, Long Chen
2022	J	`jnl`	Algorithms and Theory for Supervised Gradual Domain Adaptation. CoRR Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
2022	J	`jnl`	Algorithms and Theory for Supervised Gradual Domain Adaptation. Trans. Mach. Learn. Res. Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
2022	Misc	`conf`	Cascading Bandit Under Differential Privacy. ICASSP Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li
2022	A	`conf`	Combinatorial Bandits under Strategic Manipulations. WSDM Jing Dong, Ke Li, Shuai Li, Baoxiang Wang
2022	A*	`conf`	Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning. ICML Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Changjie Fan, Fei Wu, Jun Xiao
2022	J	`jnl`	Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. CoRR Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
2022	J	`jnl`	Learning From Good Trajectories in Offline Multi-Agent Reinforcement Learning. CoRR Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang
2022	J	`jnl`	Online Policy Optimization for Robust MDP. CoRR Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
2022	J	`jnl`	Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation. CoRR Jing Dong, Li Shen, Yinggan Xu, Baoxiang Wang
2021	J	`jnl`	Cascading Bandit under Differential Privacy. CoRR Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li, Shuo Shao
2021	J	`jnl`	Combinatorial Bandits under Strategic Manipulations. CoRR Jing Dong, Ke Li, Shuai Li, Baoxiang Wang
2021	J	`jnl`	Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient. CoRR Shanchao Yang, Kaili Ma, Baoxiang Wang, Hongyuan Zha
2021	J	`jnl`	Incentivizing an Unknown Crowd. CoRR Jing Dong, Shuai Li, Baoxiang Wang
2021	J	`jnl`	Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth. CoRR Qi Tian, Kun Kuang, Baoxiang Wang, Furui Liu, Fei Wu
2021	J	`jnl`	Multilinear extension of k-submodular functions. CoRR Baoxiang Wang, Huanjian Zhou
2021	A*	`conf`	Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. KDD Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao
2021	J	`jnl`	Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. CoRR Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao
2020	A	`conf`	Learning and Testing Variable Partitions. ITCS Andrej Bogdanov, Baoxiang Wang
2020	J	`jnl`	Learning and Testing Variable Partitions. CoRR Andrej Bogdanov, Baoxiang Wang
2020	A*	`conf`	The Gambler's Problem and Beyond. ICLR Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan
2020	J	`jnl`	The Gambler's Problem and Beyond. CoRR Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan
2019	—	`conf`	Beyond Winning and Losing: Modeling Human Motivations and Behaviors with Vector-Valued Inverse Reinforcement Learning. AIIDE Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng
2019	A*	`conf`	Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control. IJCAI Kenny Young, Baoxiang Wang, Matthew E. Taylor
2019	A*	`conf`	Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces. NeurIPS Baoxiang Wang, Nidhi Hegde
2019	J	`jnl`	Private Q-Learning with Functional Noise in Continuous Spaces. CoRR Baoxiang Wang, Nidhi Hegde
2019	A*	`conf`	Recurrent Existence Determination Through Policy Optimization. IJCAI Baoxiang Wang
2019	J	`jnl`	Recurrent Existence Determination Through Policy Optimization. CoRR Baoxiang Wang
2018	J	`jnl`	Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning. CoRR Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng
2018	J	`jnl`	Metatrace: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control. CoRR Kenny Young, Baoxiang Wang, Matthew E. Taylor
2018	—	`conf`	Policy Optimization with Second-Order Advantage Information. ICLR (Workshop) Jiajin Li, Baoxiang Wang
2018	A*	`conf`	Policy Optimization with Second-Order Advantage Information. IJCAI Jiajin Li, Baoxiang Wang, Shengyu Zhang
2018	J	`jnl`	Policy Optimization with Second-Order Advantage Information. CoRR Jiajin Li, Baoxiang Wang
2016	A*	`conf`	Contextual Combinatorial Cascading Bandits. ICML Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen
2015	A	`conf`	PAID: Prioritizing app issues for developers by tracking user reviews over versions. ISSRE Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu