[2603.04819] On the Strengths and Weaknesses of Data for Open-set Embodied Assistance

Computer Science > Robotics arXiv:2603.04819 (cs) [Submitted on 5 Mar 2026] Title:On the Strengths and Weaknesses of Data for Open-set Embodied Assistance Authors:Pradyumna Tambwekar, Andrew Silva, Deepak Gopinath, Jonathan DeCastro, Xiongyi Cui, Guy Rosman View a PDF of the paper titled On the Strengths and Weaknesses of Data for Open-set Embodied Assistance, by Pradyumna Tambwekar and 5 other authors View PDF Abstract:Embodied foundation models are increasingly performant in real-world domains such as robotics or autonomous driving. These models are often deployed in interactive or assistive settings, where it is important that these assistive models generalize to new users and new tasks. Diverse interactive data generation offers a promising avenue for providing data-efficient generalization capabilities for interactive embodied foundation models. In this paper, we investigate the generalization capabilities of a multimodal foundation model fine-tuned on diverse interactive assistance data in a synthetic domain. We explore generalization along two axes: a) assistance with unseen categories of user behavior and b) providing guidance in new configurations not encountered during training. We study a broad capability called \textbf{Open-Set Corrective Assistance}, in which the model needs to inspect lengthy user behavior and provide assistance through either corrective actions or language-based feedback. This task remains unsolved in prior work, which typically assumes clos...