Xiaoyang Xu
Papers
1
Total Citations
2
H-Index
1
About
Xiaoyang Xu is a pioneering researcher at the intersection of embodied intelligence, vision-language models, and robotics, with a focus on bridging the gap between general AI systems and real-world home applications. Their most notable contribution is the development of **SweepMM**, a high-quality multimodal dataset specifically designed for sweeping robots in home scenarios. This work addresses a critical bottleneck in embodied AI: while general vision-language models excel in broad tasks, they fail to understand domain-specific knowledge required for domestic robotics. By curating SweepMM, Xu enables vision-language models to learn nuanced interactions within household environments, advancing the goal of general intelligence through grounded, real-world learning. Although recently published in 2024, the paper has already garnered attention with 2 citations, signaling its potential to influence future research in home robotics and multimodal learning. Xu’s work is particularly impactful for students and researchers exploring how to adapt large-scale AI models to specialized, practical domains—a key step toward truly intelligent, autonomous home assistants.
Research Focus
Key Achievements
Top Papers
- 1