activity
20232026
most citedEmbodied AI Agents: Modeling the World

9 citations · 9 across the 5 of their papers we have counts for

collaborators

6 papers

cs.RO2026

Cross-Embodiment Robot Foundation World Models with Latent Actions

Huang Huang, Sriram Yenamandra, Arjun Majumdar +9

The diversity of robot embodiments and action spaces makes it challenging to build robot world models that generalize across different embodiments. We introduce the Latent Action-C…

cs.RO2026

DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning

Hanchen Cui, Sergio Arnaud, Arjun Majumdar +5

Pretrained vision-language-action (VLA) policies show promising zero-shot generalization, but often fail under deployment-time distribution shift, leading to decreased robustness a…

cs.AI2026

Voxtral Realtime

Mistral-AI, :, Alexander H. Liu +166

We introduce Voxtral Realtime, a natively streaming automatic speech recognition model that matches offline transcription quality at sub-second latency. Unlike approaches that adap…

cs.AI2025★ 9 cited

Embodied AI Agents: Modeling the World

Pascale Fung, Yoram Bachrach, Asli Celikyilmaz +18

This paper describes our research on AI agents embodied in visual, virtual or physical forms, enabling them to interact with both users and their environments. These agents, which…

cs.CV2025

Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D

Sergio Arnaud, Paul McVay, Ada Martin +19

We present LOCATE 3D, a model for localizing objects in 3D scenes from referring expressions like "the small coffee table between the sofa and the lamp." LOCATE 3D sets a new state…

cs.RO2023

Stretch with Stretch: Physical Therapy Exercise Games Led by a Mobile Manipulator

Matthew Lamsey, You Liang Tan, Meredith D. Wells +10

Physical therapy (PT) is a key component of many rehabilitation regimens, such as treatments for Parkinson's disease (PD). However, there are shortages of physical therapists and a…