6 papers
Crayotter: Traceable Multi-Agent Workflows for Long-Form Video Editing
Lecheng Yan, Yichong Zhang, Xiantao Xu +12
Long-form video editing over heterogeneous footage requires agents to coordinate source selection, multimodal analysis, timeline construction, narration and subtitle alignment, ren…
Distributional Inverse Reinforcement Learning
Feiyang Wu, Ye Zhao, Anqi Wu
We propose a distributional framework for offline Inverse Reinforcement Learning (IRL) that jointly models uncertainty over reward functions and full distributions of returns. Unli…
Hierarchical Diffusion Motion Planning with Task-Conditioned Uncertainty-Aware Priors
Amelie Minji Kim, Anqi Wu, Ye Zhao
We propose a novel hierarchical diffusion planner that embeds task and motion structure directly into the noise model. Unlike standard diffusion-based planners that rely on zero-me…
EmoBipedNav: Emotion-aware Social Navigation for Bipedal Robots with Deep Reinforcement Learning
Wei Zhu, Abirath Raju, Abdulaziz Shamsah +3
This study presents an emotion-aware navigation framework -- EmoBipedNav -- using deep reinforcement learning (DRL) for bipedal robots walking in socially interactive environments.…
Learn to Teach: Sample-Efficient Privileged Learning for Humanoid Locomotion over Diverse Terrains
Feiyang Wu, Xavier Nal, Jaehwi Jang +4
Humanoid robots promise transformative capabilities for industrial and service applications. While recent advances in Reinforcement Learning (RL) yield impressive results in locomo…
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang +2
Traditional approaches to studying decision-making in neuroscience focus on simplified behavioral tasks where animals perform repetitive, stereotyped actions to receive explicit re…