1 citations · 1 across the 11 of their papers we have counts for
11 papers
Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents
Haoran Zhang, Yifu Lu, Boyang Wang +5
Long-horizon tasks are common in real-world robotic deployments, yet failure detection for such tasks remains underexplored. Detecting failures in long-horizon robotic tasks is par…
TBD-VLA: Temporal Block Diffusion Vision Language Action Model
Sung-Wook Lee, Xuhui Kang, Yen-Ling Kuo
Discrete Vision-Language-Action (VLA) models typically formulate action generation as next-token prediction over discretized action spaces, conditioning each token autoregressively…
Learning Force-Regulated Robotic Manipulation with a Low-Cost Tactile-Force-Controlled Gripper
Xuhui Kang, Tongxuan Tian, Sung-Wook Lee +3
Successfully manipulating many everyday objects, such as potato chips, requires precise force regulation. Failure to modulate force can lead to task failure or irreversible damage…
Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning
Alex Ning, Yen-Ling Kuo, Gabe Gomes
Latent reasoning represents a new development in Transformer language models that has shown potential in compressing reasoning lengths compared to chain-of-thought reasoning. By di…
OAfford: One-Shot 3D Object-to-Object Affordance Grounding for Generalizable Robotic Manipulation
Tongxuan Tian, Xuhui Kang, Yen-Ling Kuo
Grounding object affordance is fundamental to robotic manipulation as it establishes the critical link between perception and action among interacting objects. However, prior works…
CLASS: Contrastive Learning via Action Sequence Supervision for Robot Manipulation
Sung-Wook Lee, Xuhui Kang, Brandon Yang +1
Recent advances in Behavior Cloning (BC) have led to strong performance in robotic manipulation, driven by expressive models, sequence modeling of actions, and large-scale demonstr…
Moving Out: Physically-grounded Human-AI Collaboration
Xuhui Kang, Sung-Wook Lee, Haolin Liu +2
The ability to adapt to physical actions and constraints in an environment is crucial for embodied agents (e.g., robots) to effectively collaborate with humans. Such physically gro…
CaseEdit: Enhancing Localized Commonsense Reasoning via Null-Space Constrained Knowledge Editing in Small Parameter Language Models
Varun Reddy, Yen-Ling Kuo
Large language models (LLMs) exhibit strong performance on factual recall and general reasoning but struggle to adapt to user-specific, commonsense knowledge, a challenge particula…
Diff-DAgger: Uncertainty Estimation with Diffusion Policy for Robotic Manipulation
Sung-Wook Lee, Xuhui Kang, Yen-Ling Kuo
Recently, diffusion policy has shown impressive results in handling multi-modal tasks in robotic manipulation. However, it has fundamental limitations in out-of-distribution failur…
Incorporating Task Progress Knowledge for Subgoal Generation in Robotic Manipulation through Image Edits
Xuhui Kang, Yen-Ling Kuo
Understanding the progress of a task allows humans to not only track what has been done but also to better plan for future goals. We demonstrate TaKSIE, a novel framework that inco…
NashFormer: Leveraging Local Nash Equilibria for Semantically Diverse Trajectory Prediction
Justin Lidard, Oswin So, Yanxia Zhang +8
Interactions between road agents present a significant challenge in trajectory prediction, especially in cases involving multiple agents. Because existing diversity-aware predictor…