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cs.RO2026

Supervise What Survives: Geometry-Guided VLA Adaptation from Synthetic Robot Videos

Danze Chen, Yanzhe Chen, Qiming Huang +3

Vision-Language-Action (VLA) models require large-scale video-action pairs, yet real teleoperation remains scarce. While generated robot videos offer a scalable alternative, existi…

cs.RO2026

ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics

Ziyu Wei, Luting Wang, Chen Gao +2

Most existing vision-language manipulation research targets rigid robotic arms, whose fixed morphology limits adaptability in cluttered or confined spaces. Soft robotic arms offer…

cs.RO2026

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform

Yu Shang, Yinzhou Tang, Yiding Ma +22

World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…

cs.RO2026

Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation

Yanzhe Chen, Kevin Yuchen Ma, Qi Lv +4

While Vision-Language-Action (VLA) models offer broad general capabilities, deploying them on specific hardware requires real-world adaptation to bridge the embodiment gap. Since r…

cs.RO2025

EVOLVE-VLA: Test-Time Training from Environment Feedback for Vision-Language-Action Models

Zechen Bai, Chen Gao, Mike Zheng Shou

Achieving truly adaptive embodied intelligence requires agents that learn not just by imitating static demonstrations, but by continuously improving through environmental interacti…