activity
20242026
most citedRobotMover: Learning to Move Large Objects From Human Demonstrations

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 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.AI2025

ADAPT: Actively Discovering and Adapting to Preferences for any Task

Maithili Patel, Xavier Puig, Ruta Desai +4

Assistive agents should be able to perform under-specified long-horizon tasks while respecting user preferences. We introduce Actively Discovering and Adapting to Preferences for a…

cs.RO2025★ 1 cited

RobotMover: Learning to Move Large Objects From Human Demonstrations

Tianyu Li, Joanne Truong, Jimmy Yang +4

Moving large objects, such as furniture or appliances, is a critical capability for robots operating in human environments. This task presents unique challenges, including whole-bo…

cs.RO2024

PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks

Matthew Chang, Gunjan Chhablani, Alexander Clegg +17

We present a benchmark for Planning And Reasoning Tasks in humaN-Robot collaboration (PARTNR) designed to study human-robot coordination in household activities. PARTNR tasks exhib…

cs.HC2024

Situated Instruction Following

So Yeon Min, Xavi Puig, Devendra Singh Chaplot +6

Language is never spoken in a vacuum. It is expressed, comprehended, and contextualized within the holistic backdrop of the speaker's history, actions, and environment. Since human…