Pan, Ling

39 publications

ICCV 2025 Beyond the Destination: A Novel Benchmark for Exploration-Aware Embodied Question Answering Kaixuan Jiang, Yang Liu, Weixing Chen, Jingzhou Luo, Ziliang Chen, Ling Pan, Guanbin Li, Liang Lin

TMLR 2025 Evolution Guided Generative Flow Networks Zarif Ikram, Ling Pan, Dianbo Liu

AAAI 2025 Flow Factorization for Efficient Generative Flow Networks Jiashun Liu, Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan

NeurIPS 2025 Learning Intractable Multimodal Policies with Reparameterization and Diversity Regularization Ziqi Wang, Jiashun Liu, Ling Pan

CVPR 2025 Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation Taeyoung Yun, Dinghuai Zhang, Jinkyoo Park, Ling Pan

ICLR 2025 Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets Haoran He, Can Chang, Huazhe Xu, Ling Pan

NeurIPS 2025 Measure Gradients, Not Activations! Enhancing Neuronal Activity in Deep Reinforcement Learning Jiashun Liu, Zihao Wu, Johan Obando-Ceron, Pablo Samuel Castro, Aaron Courville, Ling Pan

ICLR 2025 Neuroplastic Expansion in Deep Reinforcement Learning Jiashun Liu, Johan Samir Obando Ceron, Aaron Courville, Ling Pan

ICLRW 2025 Pre-Trained Video Generative Models as World Simulators Haoran He, Yang Zhang, Liang Lin, Zhongwen Xu, Ling Pan

ICML 2025 Random Policy Evaluation Uncovers Policies of Generative Flow Networks Haoran He, Emmanuel Bengio, Qingpeng Cai, Ling Pan

ICLRW 2025 Small Features Matter: Robust Representation for World Models Zarif Ikram, Miranda Anna Christ, Ling Pan, Dianbo Liu

ICML 2025 The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning Jiashun Liu, Johan Obando-Ceron, Pablo Samuel Castro, Aaron Courville, Ling Pan

AAAI 2025 Towards Robust, Efficient, and Practical Decision-Making: From Reward-Maximizing Deep Reinforcement Learning to Reward-Matching GFlowNets Ling Pan

CoRL 2024 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

TMLR 2024 Distributional GFlowNets with Quantile Flows Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron Courville, Yoshua Bengio

ICLRW 2024 Evolution Guided Generative Flow Networks Zarif Ikram, Ling Pan, Dianbo Liu

NeurIPS 2024 Kaleidoscope: Learnable Masks for Heterogeneous Multi-Agent Reinforcement Learning Xinran Li, Ling Pan, Jun Zhang

NeurIPS 2024 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

ICML 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woo Chang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio

ICLR 2024 Pre-Training and Fine-Tuning Generative Flow Networks Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio

NeurIPS 2024 QGFN: Controllable Greediness with Action Values Elaine Lau, Stephen Zhewen Lu, Ling Pan, Doina Precup, Emmanuel Bengio

ICMLW 2024 QGFN: Controllable Greediness with Action Values Elaine Lau, Stephen Zhewen Lu, Ling Pan, Doina Precup, Emmanuel Bengio

NeurIPS 2024 Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training Pihe Hu, Shaolong Li, Zhuoran Li, Ling Pan, Longbo Huang

ICML 2023 Better Training of GFlowNets with Local Credit and Incomplete Trajectories Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio

ICLR 2023 Generative Augmented Flow Networks Ling Pan, Dinghuai Zhang, Aaron Courville, Longbo Huang, Yoshua Bengio

NeurIPSW 2023 Learning to Scale Logits for Temperature-Conditional GFlowNets Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woo Chang Kim, Jinkyoo Park, Yoshua Bengio

NeurIPS 2023 Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan

NeurIPSW 2023 Pre-Training and Fine-Tuning Generative Flow Networks Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio

NeurIPSW 2023 Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries Zarif Ikram, Ling Pan, Dianbo Liu

ICLR 2023 RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch Yiqin Tan, Pihe Hu, Ling Pan, Jiatai Huang, Longbo Huang

UAI 2023 Stochastic Generative Flow Networks Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio

NeurIPS 2022 E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu

ICML 2022 Plan Better amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification Ling Pan, Longbo Huang, Tengyu Ma, Huazhe Xu

NeurIPSW 2021 Plan Better amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification Ling Pan, Longbo Huang, Tengyu Ma, Huazhe Xu

NeurIPS 2021 Regularized SoftMax Deep Multi-Agent Q-Learning Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson

AAAI 2020 Deterministic Value-Policy Gradients Qingpeng Cai, Ling Pan, Pingzhong Tang

IJCAI 2020 Reinforcement Learning with Dynamic Boltzmann SoftMax Updates Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang

NeurIPS 2020 SoftMax Deep Double Deterministic Policy Gradients Ling Pan, Qingpeng Cai, Longbo Huang

AAAI 2019 A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, Longbo Huang