collaborators

8 papers

cs.RO2026

ActiveArena: Benchmarking and Understanding Active Perception in Robotic Manipulation

Yibo Li, Enshen Zhou, Rui Chen +7

Active perception and manipulation are crucial for robots to interact with complex scenes. Existing benchmarks struggle to evaluate how robots effectively acquire and maintain info…

cs.CV2026

Building a Precise Video Language with Human-AI Oversight

Zhiqiu Lin, Chancharik Mitra, Siyuan Cen +13

Video-language models (VLMs) learn to reason about the dynamic visual world through natural language. We introduce a suite of open datasets, benchmarks, and recipes for scalable ov…

cs.RO2026

SaPaVe: Towards Active Perception and Manipulation in Vision-Language-Action Models for Robotics

Mengzhen Liu, Enshen Zhou, Cheng Chi +6

Active perception and manipulation are crucial for robots to interact with complex scenes. Existing methods struggle to unify semantic-driven active perception with robust, viewpoi…

cs.RO2026

RoboBrain 2.5: Depth in Sight, Time in Mind

Huajie Tan, Enshen Zhou, Zhiyu Li +32

We introduce RoboBrain 2.5, a next-generation embodied AI foundation model that advances general perception, spatial reasoning, and temporal modeling through extensive training on…

cs.RO2025

Towards Spatial Trace with Reasoning in Vision-Language Models for Robotics

Enshen Zhou, Yibo Li, Jingkun An +12

Spatial tracing, as a fundamental embodied interaction ability for robots, is inherently challenging as it requires multi-step metric-grounded reasoning compounded with complex spa…

cs.RO2025

TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics

Yi Han, Enshen Zhou, Shanyu Rong +6

Vision-Language Models (VLMs) have shown remarkable capabilities in spatial reasoning, yet they remain fundamentally limited to qualitative precision and lack the computational pre…

cs.RO2025

RoboBrain 2.0 Technical Report

BAAI RoboBrain Team, Mingyu Cao, Huajie Tan +50

We introduce RoboBrain 2.0, our latest generation of embodied vision-language foundation models, designed to unify perception, reasoning, and planning for complex embodied tasks in…

cs.RO2025

RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics

Enshen Zhou, Jingkun An, Cheng Chi +8

Spatial referring is a fundamental capability of embodied robots to interact with the 3D physical world. However, even with the powerful pretrained vision language models (VLMs), r…