4 papers
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…
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…