Xuye Wang
Papers
1
Total Citations
7
H-Index
1
About
Xuye Wang is a leading researcher at the intersection of artificial intelligence and robotics, with a primary focus on integrating large language models (LLMs) into real-time robotic systems. Their most notable contribution is the development of LAMARS (Large Language Model-Based Anticipation Mechanism Acceleration in Real-Time Robotic Systems), a groundbreaking framework that addresses the critical challenge of deploying LLMs in time-sensitive robotic applications. This work, published in 2024 and already garnering 7 citations, demonstrates how LLMs can be effectively leveraged for robotic inference and task handling while overcoming latency constraints. Wang's research fundamentally advances the field by enabling robots to harness the extensive knowledge embedded in LLMs for real-time decision-making, bridging the gap between sophisticated AI reasoning and practical robotic execution. Their work represents a significant step toward more intelligent, responsive autonomous systems that can operate in dynamic environments. As the field of embodied AI continues to evolve rapidly, Wang's contributions are proving instrumental in shaping how next-generation robots will perceive, reason, and act in the physical world.
Research Focus
Key Achievements
Top Papers
- 1