activity
20242026
most citedLongCat-Flash Technical Report

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Robust and Generalized Humanoid Motion Tracking

Yubiao Ma, Han Yu, Jiayin Xie +7

Learning a general humanoid whole-body controller is challenging because practical reference motions can exhibit noise and inconsistencies after being transferred to the robot doma…

cs.CL2025★ 1 cited

LongCat-Flash Technical Report

Meituan LongCat Team, Bayan, Bei Li +179

We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…

cs.AI2025

Introducing LongCat-Flash-Thinking: A Technical Report

Meituan LongCat Team, Anchun Gui, Bei Li +122

We present LongCat-Flash-Thinking, an efficient 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model. Its advanced capabilities are cultivated through a metic…

cs.RO2025

Astra: Toward General-Purpose Mobile Robots via Hierarchical Multimodal Learning

Sheng Chen, Peiyu He, Jiaxin Hu +67

Modern robot navigation systems encounter difficulties in diverse and complex indoor environments. Traditional approaches rely on multiple modules with small models or rule-based s…

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…

cs.RO2025

DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion

Yahao Fan, Tianxiang Gui, Kaiyang Ji +8

Achieving versatile humanoid locomotion with a single policy presents a critical scalability challenge. Prevailing methods often rely on distilling multiple terrain-specific teache…

cs.RO2024

Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots

Xuancun Lu, Zhengxian Huang, Xinfeng Li +4

LLM-based robots use Large Language Models (LLMs) as planners to translate natural language instructions into policies such as grasp(), move_to(), and open_gripper(). Jailbreak att…