activity
20242026
most citedMoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2026

H-VLA: Hierarchical Vision-Language-Action Model with Key-Action Reasoning and Motion Planning in a Unified Action Space

Xiongfeng Peng, Lu Xu, Yandong Wang +10

Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but many existing methods still rely on direct mappings from language and visual observati…

cs.CV2026

Referring Layer Decomposition

Fangyi Chen, Yaojie Shen, Lu Xu +4

Precise, object-aware control over visual content is essential for advanced image editing and compositional generation. Yet, most existing approaches operate on entire images holis…

cs.AI2025★ 1 cited

MoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines

Lu Xu, Jiaqian Yu, Xiongfeng Peng +7

To meet the growing demand for smarter, faster, and more efficient embodied AI solutions, we introduce a novel Mixture-of-Expert (MoE) method that significantly boosts reasoning an…

cs.CV2025

Pushing Trade-Off Boundaries: Compact yet Effective Remote Sensing Change Detection

Luosheng Xu, Dalin Zhang, Zhaohui Song

Remote sensing change detection is essential for monitoring urban expansion, disaster assessment, and resource management, offering timely, accurate, and large-scale insights into…

cs.CV2024

NTIRE 2024 Challenge on Night Photography Rendering

Egor Ershov, Artyom Panshin, Oleg Karasev +47

This paper presents a review of the NTIRE 2024 challenge on night photography rendering. The goal of the challenge was to find solutions that process raw camera images taken in nig…