8 papers
An Informational Curse of Horizon in Goal-Conditioned Policy Learning
John L. Zhou, Yuxuan Dong, Jonathan C. Kao
The difficulty of learning goal-reaching policies is often attributed to a "curse of horizon" that manifests as bias accumulation in temporal-difference backups and noisy advantage…
Steering Autoregressive Vision-Language-Action Policies via Action Token Intervention
Jason Chan, Jonathan C. Kao
We present Token Steering (TS), a method for dynamically steering trajectories generated by an autoregressive vision-language-action (VLA) model through direct intervention in the…
Flow Control: Steering Vision-Language-Action Models with Simple Real-Time Inputs
Jonathan C. Kao, Jason Chan, Andy Wang
We introduce flow control of vision-language-action (VLA) models, a simple and effective way to steer VLA actions in real time through generic inputs, such as a keyboard. This meth…
Intent at a Glance: Gaze-Guided Robotic Manipulation via Foundation Models
Tracey Yee Hsin Tay, Xu Yan, Jonathan Ouyang +4
Designing intuitive interfaces for robotic control remains a central challenge in enabling effective human-robot interaction, particularly in assistive care settings. Eye gaze offe…
LowKeyEMG: Electromyographic typing with a reduced keyset
Johannes Y. Lee, Derek Xiao, Shreyas Kaasyap +6
We introduce LowKeyEMG, a real-time human-computer interface that enables efficient text entry using only 7 gesture classes decoded from surface electromyography (sEMG). Prior work…
Flattening Hierarchies with Policy Bootstrapping
John L. Zhou, Jonathan C. Kao
Offline goal-conditioned reinforcement learning (GCRL) is a promising approach for pretraining generalist policies on large datasets of reward-free trajectories, akin to the self-s…
Shared Autonomy with IDA: Interventional Diffusion Assistance
Brandon J. McMahan, Zhenghao Peng, Bolei Zhou +1
The rapid development of artificial intelligence (AI) has unearthed the potential to assist humans in controlling advanced technologies. Shared autonomy (SA) facilitates control by…
Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents
John L. Zhou, Weizhe Hong, Jonathan C. Kao
Cooperation between self-interested individuals is a widespread phenomenon in the natural world, but remains elusive in interactions between artificially intelligent agents. Instea…