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Ling Pan

28 papers · 2019–2026 · 9 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ 🌍 Conference Polyglot (9) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (6)
πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (13) πŸ—ΊοΈ Taxonomy Completionist (37) πŸ‘‘ Triple Crown πŸ† Keyword Champion (3) 🧬 Topic Evolution πŸ† Grand Slam πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (99) πŸ’Ž Century Club (27) ⚑ Prolific Year (7) πŸš€ Conference Pioneer

Conferences

NIPS (8) AAAI (5) ICLR (5) ICML (5) CORL (1) CVPR (1) ICCV (1) IJCAI (1) UAI (1)

Top co-authors

Longbo Huang (9) Yoshua Bengio (6) Qingpeng Cai (6) Dinghuai Zhang (6) Haoran He (5) Emmanuel Bengio (3) Jiashun Liu (3) Aaron Courville (3) Huazhe Xu (3) Pihe Hu (2)

Keywords

generative flow network (6) deep reinforcement learning (3) multi-agent reinforcement learning (3) deep deterministic policy gradient (3) reinforcement learning (3) video generation (2) model-based reinforcement learning (2) softmax operator (2) energy-based model (2) value function (2) continuous control (2) diffusion model (2) video prediction (1) sample efficiency (1) probabilistic inference (1) policy gradient (1) stochastic processes (1) variational inference (1) markov chain monte carlo (1) probabilistic modeling (1)

Papers

Pre-Trained Video Generative Models as World Simulators AAAI 2026 Beyond the Destination: A Novel Benchmark for Exploration-Aware Embodied Question Answering ICCV 2025 Flow Factorization for Efficient Generative Flow Networks AAAI 2025 Towards Robust, Efficient, and Practical Decision-Making: From Reward-Maximizing Deep Reinforcement Learning to Reward-Matching GFlowNets AAAI 2025 Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation CVPR 2025 Neuroplastic Expansion in Deep Reinforcement Learning ICLR 2025 Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets ICLR 2025 Random Policy Evaluation Uncovers Policies of Generative Flow Networks ICML 2025 The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning ICML 2025 Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective CORL 2024 Pre-Training and Fine-Tuning Generative Flow Networks ICLR 2024 Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training NIPS 2024 Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training NIPS 2024 Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning NIPS 2024 QGFN: Controllable Greediness with Action Values NIPS 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets ICML 2024 Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets NIPS 2023 Better Training of GFlowNets with Local Credit and Incomplete Trajectories ICML 2023 Stochastic Generative Flow Networks UAI 2023 RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch ICLR 2023 Generative Augmented Flow Networks ICLR 2023 E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance NIPS 2022 Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification ICML 2022 Regularized Softmax Deep Multi-Agent Q-Learning NIPS 2021 Reinforcement Learning with Dynamic Boltzmann Softmax Updates IJCAI 2020 Softmax Deep Double Deterministic Policy Gradients NIPS 2020 Deterministic Value-Policy Gradients AAAI 2020 A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems AAAI 2019