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20242026
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cs.RO2026

Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models

Li Wenjie, Yash Jangir, Ignacy Stepka +3

Action verbs describe not only the physical outcomes of actions, but also how those actions are performed. Yet action representations in vision-language-action models (VLAs) are ty…

cs.RO2026

IndoorR2X: Indoor Robot-to-Everything Coordination with LLM-Driven Planning

Fan Yang, Soumya Teotia, Shaunak A. Mehta +8

Although robot-to-robot (R2R) communication improves indoor scene understanding beyond what a single robot can achieve, R2R alone cannot overcome partial observability without subs…

cs.RO2026

ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies

Andrew Zou Li, Gokul Swamy, Yonatan Bisk +1

Generative control policies (GCPs), such as diffusion policies and flow-based vision-language-action models, enable test-time scaling in robot control. Test-time compute can be all…

cs.RO2026

Flatness Preserves Instruction Following in Vision-Language-Action Models

Haochen Zhang, Yonatan Bisk

Vision-language-action (VLA) models have the potential for open-world generalization by leveraging pretrained vision-language representations, yet downstream finetuning on limited…

cs.RO2026

Inductive Generalization for Robotic Manipulation

Annabella Macaluso, Haochen Zhang, Ishaan Masilamony +2

Understanding the generalization capabilities of visuomotor policies is essential in the development of capable robotic agents. Generalizable models learn structures that transfer…

cs.RO2026

RobotArena : Scalable Robot Benchmarking via Real-to-Sim Translation

Yash Jangir, Yidi Zhang, Pang-Chi Lo +7

The pursuit of robot generalists, agents capable of performing diverse tasks across diverse environments, demands rigorous and scalable evaluation. Yet real-world testing of robot…