most citedTheory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

I3L: Iterative Interactive Imitation Learning for Whole-Body Mobile Manipulation

Wensi Ai, Christopher Luey, Karthik Dharmarajan +7

Policies trained offline from teleoperated demonstrations can degrade outside their training distribution. This gap is particularly acute in long-horizon whole-body mobile manipula…

cs.RO2026

MANIGUARD: A Benchmark and Data Suite for Specification-Grounded Safety Evaluation and Improvement of Robotic Manipulation

Yiyan Peng, Philip Wang, Simon Sinong Zhan +11

Foundation-model policies for robotic manipulation are advancing rapidly on task success, but rigorous evaluation of whether they succeed safely is still lacking. We introduce Mani…

cs.RO2026

Behavior Uncloning: Distilling Mode Redirection into Policy Weights without Inference-Time Steering

Hao Wang, Jiuzhou Lei, Dayou Li +5

Behavior-cloned policies often learn multiple behavior modes from demonstration datasets, including modes that are unsafe or otherwise undesired at deployment. For example, a polic…

cs.AI2026★ 1 cited

Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?

Pingyue Zhang, Zihan Huang, Yue Wang +11

Spatial embodied intelligence requires agents to act to acquire information under partial observability. While multimodal foundation models excel at passive perception, their capac…

cs.AI2025

ENACT: Evaluating Embodied Cognition with World Modeling of Egocentric Interaction

Qineng Wang, Wenlong Huang, Yu Zhou +8

Embodied cognition argues that intelligence arises from sensorimotor interaction rather than passive observation. It raises an intriguing question: do modern vision-language models…

cs.RO2025

MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation

Chengshu Li, Mengdi Xu, Arpit Bahety +11

Imitation learning from large-scale, diverse human demonstrations has been shown to be effective for training robots, but collecting such data is costly and time-consuming. This ch…

cs.RO2025

BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities

Yunfan Jiang, Ruohan Zhang, Josiah Wong +7

Real-world household tasks present significant challenges for mobile manipulation robots. An analysis of existing robotics benchmarks reveals that successful task performance hinge…