Bei Peng - RankMe

46 papers A* 10A 3B 1C 1Journal 24Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Heuristic Transformer: Belief Augmented In-Context Reinforcement Learning. CoRR Oliver Dippel, Alexei Lisitsa, Bei Peng
2025	J	`jnl`	Rethinking Cross-Generator Image Forgery Detection through DINOv3. CoRR Zhenglin Huang, Jason Li, Haiquan Wen, Tianxiao Li, Xi Yang, Lu Qi, Bei Peng, Xiaowei Huang, Ming-Hsuan Yang, Guangliang Cheng
2025	A*	`conf`	SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model. CVPR Zhenglin Huang, Jinwei Hu, Xiangtai Li, Yiwei He, Xingyu Zhao, Bei Peng, Baoyuan Wu, Xiaowei Huang, Guangliang Cheng
2025	J	`jnl`	So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection. CoRR Zhenglin Huang, Tianxiao Li, Xiangtai Li, Haiquan Wen, Yiwei He, Jiangning Zhang, Hao Fei, Xi Yang, Xiaowei Huang, Bei Peng, Guangliang Cheng
2024	—	`conf`	Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping. CASE Gabriella Pizzuto, Hetong Wang, Hatem Fakhruldeen, Bei Peng, Kevin S. Luck, Andrew I. Cooper
2024	—	`conf`	Contextual Transformers for Goal-Oriented Reinforcement Learning. SGAI Conf. (1) Oliver Dippel, Alexei Lisitsa, Bei Peng
2024	J	`jnl`	SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model. CoRR Zhenglin Huang, Jinwei Hu, Xiangtai Li, Yiwei He, Xingyu Zhao, Bei Peng, Baoyuan Wu, Xiaowei Huang, Guangliang Cheng
2023	—	`conf`	Deep Reinforcement Learning for Continuous Control of Material Thickness. SGAI Conf. Oliver Dippel, Alexei Lisitsa, Bei Peng
2022	J	`jnl`	Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping. CoRR Gabriella Pizzuto, Hetong Wang, Hatem Fakhruldeen, Bei Peng, Kevin S. Luck, Andrew I. Cooper
2022	J	`jnl`	Curriculum Learning for Relative Overgeneralization. CoRR Lin Shi, Bei Peng
2022	J	`jnl`	Dependable learning-enabled multiagent systems. AI Commun. Xiaowei Huang, Bei Peng, Xingyu Zhao
2021	A*	`conf`	FACMAC: Factored Multi-Agent Centralised Policy Gradients. NeurIPS Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson
2021	A*	`conf`	RODE: Learning Roles to Decompose Multi-Agent Tasks. ICLR Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang
2021	A*	`conf`	Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning. ICML Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
2021	A*	`conf`	Regularized Softmax Deep Multi-Agent Q-Learning. NeurIPS Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson
2021	J	`jnl`	Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients. CoRR Bozhidar Vasilev, Tarun Gupta, Bei Peng, Shimon Whiteson
2021	J	`jnl`	Softmax with Regularization: Better Value Estimation in Multi-Agent Reinforcement Learning. CoRR Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson
2021	J	`jnl`	Special issue on adaptive and learning agents 2018. Knowl. Eng. Rev. Patrick Mannion, Anna Harutyunyan, Bei Peng, Kaushik Subramanian
2021	A*	`conf`	UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning. ICML Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson
2020	J	`jnl`	AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning. CoRR Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha
2020	J	`jnl`	Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. CoRR Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone
2020	J	`jnl`	Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. J. Mach. Learn. Res. Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone
2020	J	`jnl`	Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control. CoRR Christian Schröder de Witt, Bei Peng, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Böhmer, Shimon Whiteson
2020	A*	`conf`	Optimistic Exploration even with a Pessimistic Initialisation. ICLR Tabish Rashid, Bei Peng, Wendelin Boehmer, Shimon Whiteson
2020	J	`jnl`	Optimistic Exploration even with a Pessimistic Initialisation. CoRR Tabish Rashid, Bei Peng, Wendelin Böhmer, Shimon Whiteson
2020	J	`jnl`	RODE: Learning Roles to Decompose Multi-Agent Tasks. CoRR Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang
2020	J	`jnl`	Special issue on adaptive and learning agents 2019. Knowl. Eng. Rev. Patrick Mannion, Patrick MacAlpine, Bei Peng, Roxana Radulescu
2020	J	`jnl`	UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning. CoRR Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Böhmer, Shimon Whiteson
2020	A*	`conf`	Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. NeurIPS Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson
2020	J	`jnl`	Weighted QMIX: Expanding Monotonic Value Function Factorisation. CoRR Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson
2019	J	`jnl`	Interactive Learning of Environment Dynamics for Sequential Tasks. CoRR Robert T. Loftin, Bei Peng, Matthew E. Taylor, Michael L. Littman, David L. Roberts
2019	J	`jnl`	VIABLE: Fast Adaptation via Backpropagating Learned Loss. CoRR Leo Feng, Luisa M. Zintgraf, Bei Peng, Shimon Whiteson
2018	J	`jnl`	Curriculum Design for Machine Learners in Sequential Decision Tasks. IEEE Trans. Emerg. Top. Comput. Intell. Bei Peng, James MacGlashan, Robert Tyler Loftin, Michael L. Littman, David L. Roberts, Matthew E. Taylor
2017	A	`conf`	Curriculum Design for Machine Learners in Sequential Decision Tasks. AAMAS Bei Peng, James MacGlashan, Robert T. Loftin, Michael L. Littman, David L. Roberts, Matthew E. Taylor
2017	A	`conf`	How Do Humans Teach: On Curriculum Design for Machine Learners. AAMAS Bei Peng
2017	A*	`conf`	Interactive Learning from Policy-Dependent Human Feedback. ICML James MacGlashan, Mark K. Ho, Robert Tyler Loftin, Bei Peng, Guan Wang, David L. Roberts, Matthew E. Taylor, Michael L. Littman
2017	J	`jnl`	Interactive Learning from Policy-Dependent Human Feedback. CoRR James MacGlashan, Mark K. Ho, Robert Tyler Loftin, Bei Peng, David L. Roberts, Matthew E. Taylor, Michael L. Littman
2016	A	`conf`	A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans. AAMAS Bei Peng, James MacGlashan, Robert Tyler Loftin, Michael L. Littman, David L. Roberts, Matthew E. Taylor
2016	J	`jnl`	Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. Auton. Agents Multi Agent Syst. Robert T. Loftin, Bei Peng, James MacGlashan, Michael L. Littman, Matthew E. Taylor, Jeff Huang, David L. Roberts
2016	—	`conf`	Towards Behavior-Aware Model Learning from Human-Generated Trajectories. AAAI Fall Symposia Robert Tyler Loftin, James MacGlashan, Bei Peng, Matthew E. Taylor, Michael L. Littman, David L. Roberts
2015	—	`conf`	Generating Real-Time Crowd Advice to Improve Reinforcement Learning Agents. AAAI Workshop: Learning for General Competency in Video Games Gabriel Victor de la Cruz, Bei Peng, Walter Stephen Lasecki, Matthew Edmund Taylor
2015	—	`conf`	On the Ability to Provide Demonstrations on a UAS: Observing 90 Untrained Participants Abusing a Flying Robot. AAAI Fall Symposia Mitchell Scott, Bei Peng, Madeline Chili, Tanay Nigam, Francis G. Pascual, Cynthia Matuszek, Matthew E. Taylor
2015	—	`conf`	Towards Integrating Real-Time Crowd Advice with Reinforcement Learning. IUI Companion Gabriel Victor de la Cruz, Bei Peng, Walter S. Lasecki, Matthew E. Taylor
2014	A*	`conf`	A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback. AAAI Robert Tyler Loftin, James MacGlashan, Bei Peng, Matthew E. Taylor, Michael L. Littman, Jeff Huang, David L. Roberts
2014	B	`conf`	Learning something from nothing: Leveraging implicit human feedback strategies. RO-MAN Robert Tyler Loftin, Bei Peng, James MacGlashan, Michael L. Littman, Matthew E. Taylor, Jeff Huang, David L. Roberts
2012	C	`conf`	A GPU-Based Accelerator for Chinese Word Segmentation. APWeb Xiwu Gu, Ruixuan Li, Kunmei Wen, Bei Peng, Weijun Xiao