collaborators

8 papers

cs.LG2026

Write-Protected Discrete Bottlenecks for Language-Grounded World Models: A Structural Limitation and Sufficient Fix

Jiayi Fang

How should language interface with a world model's discrete symbol system? The dominant paradigm -- end-to-end injection of LLM/VLM features into robot world models (RT-2, Octo, Pa…

cs.RO2026

Embodiment Meets Environment: Toward Context-Aware, Safe Physical Caregiving Robots

Zhanxin Wu, Ruofei Tong, Jiaying Fang +1

Physical caregiving robots need to assist different users with different tasks in diverse environments, and they come in many embodiments. While substantial progress has been made…

cs.RO2026

Beyond Failure Recovery: An Engagement-Aware Human-in-the-loop Framework for Robotic Systems

Jiaying Fang, Joyce Yang, Zhanxin Wu +2

Conventional human-in-the-loop approaches typically involve users only when a robot encounters failure or uncertainty, treating humans primarily as tools for improving robot perfor…

cs.LG2026

Emergent Semantic Representations in World Models through Physical Interaction without Linguistic Supervision

Jiayi Fang

What does a world model learn from physical exploration, without any linguistic supervision? We argue the answer is organized by a single principle: the geometric structure of the…

cs.RO2026

A Human-in-the-Loop Confidence-Aware Failure Recovery Framework for Modular Robot Policies

Rohan Banerjee, Krishna Palempalli, Bohan Yang +5

Robots operating in unstructured human environments inevitably encounter failures, especially in robot caregiving scenarios. While humans can often help robots recover, excessive o…

cs.RO2025

Masquerade: Learning from In-the-wild Human Videos using Data-Editing

Marion Lepert, Jiaying Fang, Jeannette Bohg

Robot manipulation research still suffers from significant data scarcity: even the largest robot datasets are orders of magnitude smaller and less diverse than those that fueled re…

cs.RO2025

Phantom: Training Robots Without Robots Using Only Human Videos

Marion Lepert, Jiaying Fang, Jeannette Bohg

Training general-purpose robots requires learning from large and diverse data sources. Current approaches rely heavily on teleoperated demonstrations which are difficult to scale.…

cs.RO2025

Force-Aware Autonomous Robotic Surgery

Alaa Eldin Abdelaal, Jiaying Fang, Tim N. Reinhart +4

This work demonstrates the benefits of using tool-tissue interaction forces in the design of autonomous systems in robot-assisted surgery (RAS). Autonomous systems in surgery must…