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cs.RO2026

OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework

Yifan Wu, Qin Li, Nan Min +14

Tactile feedback provides embodied agents with physical information beyond visual observations, enabling more reliable interaction with the real world. However, despite the rapid p…

cs.RO2026

LIBERO-Agent: Evaluating General-Purpose Agents for Direct Embodied Manipulation

Zijie Diao, Yitong Chen, Sicheng Xie +7

General-purpose agents can plan, use tools, and revise their behavior from feedback, but it remains unclear whether these capabilities transfer from digital environments to embodie…

cs.RO2026

Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlation

Shengqi Xu, Guojin Zhong, Yang Liu +7

Visuo-Tactile policies leveraging optical tactile sensors have shown great promise in contact-rich manipulation. These sensors achieve high spatial resolution and multi-dimensional…

cs.RO2026

ThinkingVLA: Interleaved Vision and Language Reasoning for Robotic Manipulation

Tianyi Lu, Hui Zhang, Zijie Diao +8

Most Vision-Language-Action (VLA) models map observations directly to actions without explicit reasoning, limiting their capacity for reasoning-intensive long-horizon tasks. To add…

cs.RO2026

ActiveMimic: Egocentric Video Pretraining with Active Perception

Xingyao Lin, Guojin Zhong, Tianyi Lu +4

Egocentric human video offers a scalable alternative to robot data for pretraining, yet models pretrained on such video consistently underperform those pretrained on robot data. We…

cs.RO2025

Ask-to-Clarify: Resolving Instruction Ambiguity through Multi-turn Dialogue

Xingyao Lin, Xinghao Zhu, Tianyi Lu +6

Embodied agents are intelligent systems designed to perceive, reason, and act within the physical world. While the robotics community has long strived to build such versatile agent…