5 papers
RDA: Reward Design Agent for Reinforcement Learning
Hojoon Lee, Ajay Subramanian, Ben Abbatematteo +4
Reinforcement learning has enabled the acquisition of impressive robotic skills, but typically requires hand-crafted reward functions that are slow to design and difficult to align…
DigiData: Training and Evaluating General-Purpose Mobile Control Agents
Yuxuan Sun, Manchen Wang, Shengyi Qian +18
AI agents capable of controlling user interfaces have the potential to transform human interaction with digital devices. To accelerate this transformation, two fundamental building…
Benchmarking Egocentric Multimodal Goal Inference for Assistive Wearable Agents
Vijay Veerabadran, Fanyi Xiao, Nitin Kamra +10
There has been a surge of interest in assistive wearable agents: agents embodied in wearable form factors (e.g., smart glasses) who take assistive actions toward a user's goal/quer…
Synthetic Captions for Open-Vocabulary Zero-Shot Segmentation
Tim Lebailly, Vijay Veerabadran, Satwik Kottur +2
Generative vision-language models (VLMs) exhibit strong high-level image understanding but lack spatially dense alignment between vision and language modalities, as our findings in…
EgoToM: Benchmarking Theory of Mind Reasoning from Egocentric Videos
Yuxuan Li, Vijay Veerabadran, Michael L. Iuzzolino +3
We introduce EgoToM, a new video question-answering benchmark that extends Theory-of-Mind (ToM) evaluation to egocentric domains. Using a causal ToM model, we generate multi-choice…