121 citations · 654 across the 70 of their papers we have counts for
8 papers · 1 filter
Red-Teaming of Vision-Language-Action Models via Quality Diversity Environment Generation
Shihan Zhao, Henry Chen, Ya-Chuan Hsu +7
A long-standing goal in robotics is to develop generalist robots that can perform tasks across a wide range of settings, flexibly specified with images and text. Vision-Language-Ac…
FELT: Generating Tactile Signals from Vision for Visuo-Tactile Manipulation
Zinan Li, Yiyang Ling, Yuming Gu +8
Tactile sensing can improve performance in contact-rich robot manipulation. However, learning policies that use real tactile feedback typically requires demonstrations collected wi…
Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization
Ayano Hiranaka, Ya-Chuan Hsu, Stefanos Nikolaidis +2
AI assistants in human-AI collaboration often correct suboptimal human actions through behavioral feedback (e.g., alerts or steering-wheel nudges in assistive driving). Such interv…
Red-Teaming Vision-Language-Action Models via Quality Diversity Prompt Generation for Robust Robot Policies
Siddharth Srikanth, Freddie Liang, Ya-Chuan Hsu +9
Vision-Language-Action (VLA) models have significant potential to enable general-purpose robotic systems for a range of vision-language tasks. However, the performance of VLA-based…
Improving through Interaction: Searching Behavioral Representation Spaces with CMA-ES-IG
Nathaniel Dennler, Zhonghao Shi, Yiran Tao +3
Robots that interact with humans must adapt to individual users' preferences to operate effectively in human-centered environments. An intuitive and effective technique to learn no…
Optimization of Edge Directions and Weights for Mixed Guidance Graphs in Lifelong Multi-Agent Path Finding
Yulun Zhang, Varun Bhatt, Matthew C. Fontaine +2
Multi-Agent Path Finding (MAPF) aims to move agents from their start to goal vertices on a graph. Lifelong MAPF (LMAPF) continuously assigns new goals to agents as they complete cu…
Theory of Mind Guided Strategy Adaptation for Zero-Shot Coordination
Andrew Ni, Simon Stepputtis, Stefanos Nikolaidis +3
A central challenge in multi-agent reinforcement learning is enabling agents to adapt to previously unseen teammates in a zero-shot fashion. Prior work in zero-shot coordination of…
Discount Model Search for Quality Diversity Optimization in High-Dimensional Measure Spaces
Bryon Tjanaka, Henry Chen, Matthew C. Fontaine +1
Quality diversity (QD) optimization searches for a collection of solutions that optimize an objective while attaining diverse outputs of a user-specified, vector-valued measure fun…