Publications

    (* indicates equal contribution)

    Preprints

  • Neuroplastic Expansion in Deep Reinforcement Learning
    Jiashun Liu, Johan Obando-Ceron, Aaron Courville, Ling Pan
    Preprint
    [PDF]

  • Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
    Haoran He, Can Chang, Huazhe Xu, Ling Pan
    Preprint
    [PDF]

  • Rectifying Reinforcement Learning for Reward Matching
    Haoran He, Emmanuel Bengio, Qingpeng Cai, Ling Pan
    Preprint
    [PDF]

  • Flow Factorization for Efficient Generative Flow Networks
    Chunhui Li*, Jiashun Liu*, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan
    Preprint
    [PDF]

  • Quantum-Inspired Mean Field Probabilistic Model for Combinatorial Optimization Problems
    Yuhan Huang, Si Yuan Jin, Yichi Zhang, Ling Pan, Qiming Shao
    Preprint
    [PDF]

    • Publications

  • Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training
    Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, Xuelong Li
    In Thirty-Eighth Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2024
    [PDF]

  • QGFN: Controllable Greediness with Action Values
    Elaine Lau, Stephen Lu, Ling Pan, Doina Precup, Emmanuel Bengio
    In Thirty-Eighth Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2024
    [PDF] [Code]

  • Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
    Xinran Li, Ling Pan, Jun Zhang
    In Thirty-Eighth Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2024
    [PDF]

  • Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training
    Pihe Hu, Shaolong Li, Zhuoran Li, Ling Pan, Longbo Huang
    In Thirty-Eighth Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2024
    [PDF]

  • Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective
    Haoran He, Peilin Wu, Chenjia Bai, Hang Lai, Lingxiao Wang, Ling Pan, Xiaolin Hu, Weinan Zhang
    In Eighth Annual Conference on Robot Learning (CoRL), Munich, Germany, 2024
    Oral
    [PDF]

  • Learning to Scale Logits for Temperature-Conditional GFlowNets
    Minsu Kim*, Joohwan Ko*, Taeyoung Yun*, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio
    In Forty-First International Conference on Machine Learning (ICML), Vienna, Austria, 2024
    [PDF]

  • Pre-Training and Fine-Tuning Generative Flow Networks
    Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio
    In Twelfth International Conference on Learning Representations (ICLR), Vienna, Austria, 2024
    Spotlight (Top 5%)
    [PDF]

  • Distributional GFlowNets with Quantile Flows
    Dinghuai Zhang*, Ling Pan*, Ricky T.Q. Chen, Aaron Courville, Yoshua Bengio
    In Transactions on Machine Learning Research (TMLR), 2024
    [PDF] [Code]

  • Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning
    Pihe Hu, Yu Chen, Ling Pan, Zhixuan Fang, Fu Xiao, Longbo Huang
    In IEEE/ACM Transactions on Networking (TON), 2024
    [PDF]

  • Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets
    Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron Courville, Yoshua Bengio, Ling Pan
    In Thirty-Seventh Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023
    Spotlight (Top 5%)
    [PDF] [Code]

  • Better Training of GFlowNets with Local Credit and Incomplete Trajectories
    Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio
    In Fortieth International Conference on Machine Learning (ICML), Hawaii, USA, 2023
    [PDF] [Code]

  • Stochastic Generative Flow Networks
    Ling Pan*, Dinghuai Zhang*, Moksh Jain, Longbo Huang, Yoshua Bengio
    In Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI), Pittsburgh, USA, 2023
    Spotlight (Top 7%)
    [PDF] [Code]

  • Generative Augmented Flow Networks
    Ling Pan, Dinghuai Zhang, Aaron Courville, Longbo Huang, Yoshua Bengio
    In Eleventh International Conference on Learning Representations (ICLR), Kigali, Rwanda, 2023
    Spotlight (Top 5%)
    [PDF] [Code]

  • RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
    Yiqin Tan, Pihe Hu, Ling Pan, Jiatai Huang, Longbo Huang
    In Eleventh International Conference on Learning Representations (ICLR), Kigali, Rwanda, 2023
    Spotlight (Top 5%)
    [PDF] [Code]

  • E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance
    Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu
    In Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2022
    Spotlight (Top 5%)
    [PDF] [Website]

  • Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
    Ling Pan, Longbo Huang, Tengyu Ma, Huazhe Xu
    In Thirty-Ninth International Conference on Machine Learning (ICML), Baltimore, USA, 2022
    [PDF] [Code] [Website]

  • Recurrent Softmax Policy Gradient for Delay-Constrained Scheduling
    Pihe Hu, Ling Pan, Yu Chen, Zhixuan Fang, Longbo Huang
    In Twenty-Third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), Seoul, South Korea, 2022
    [PDF]

  • Network Topology Optimization via Deep Reinforcement Learning
    Zhuoran Li, Xing Wang, Ling Pan, Lin Zhu, Zhendong Wang, Junlan Feng, Chao Deng, Longbo Huang
    In IEEE Transactions on Communications (TCOM), 2022
    [PDF]

  • Regularized Softmax Deep Multi-Agent Q-Learning
    Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson
    In Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), 2021
    [PDF][Code]

  • Exploration in Policy Optimization through Multiple Paths
    Ling Pan, Qingpeng Cai, Longbo Huang
    Journal of Autonomous Agents and Multi-agent Systems (JAAMAS), 2021
    [PDF]

  • Softmax Deep Double Deterministic Policy Gradients
    Ling Pan, Qingpeng Cai, Longbo Huang
    In Thirty-Fourth Conference on Neural Information Processing Systems (NeurIPS), 2020
    [PDF][Code]

  • Reinforcement Learning with Dynamic Boltzmann Softmax Updates
    Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang
    In Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI), 2020, Yokohama, Japan
    (Acceptance rate: 12.6%)
    [PDF]

  • Multi-Path Policy Optimization
    Ling Pan, Qingpeng Cai, Longbo Huang
    In Nineteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020, Auckland, New Zealand
    Invited for fast-track publication in JAAMAS (Top 5%)
    [PDF]

  • Deterministic Value-Policy Gradients
    Qingpeng Cai*, Ling Pan*, Pingzhong Tang
    In Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020, New York, USA
    [PDF]

  • A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems
    Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, Longbo Huang
    In Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019, Hawaii, USA
    (Acceptance rate: 16.2%)
    [PDF] [Slides] [Poster]