Publications

(* indicates equal contribution)

• 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]
  

Preprints

• Large-Scale Actionless Video Pre-Training via Discrete Diffusion for Efficient Policy Learning
  Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, Xuelong Li
  [PDF]
  

• QGFN: Controllable Greediness with Action Values
  Elaine Lau, Stephen Lu, Ling Pan, Doina Precup, Emmanuel Bengio
  [PDF]
  

• Evolution Guided Generative Flow Networks
  Zarif Ikram, Ling Pan, Dianbo Liu
  [PDF]
  

• One is More: Diverse Perspectives within a Single Network for Efficient Deep Reinforcement Learning
  Yiqin Tan, Ling Pan, Longbo Huang
  Preprint
  [PDF]
  

• Beyond Conservatism: Diffusion Policies in Offline Multi-agent Reinforcement Learning
  Zhuoran Li, Ling Pan, Longbo Huang
  Preprint
  [PDF]