Jinyue Yan
Papers
1
Total Citations
105
H-Index
1
About
Jinyue Yan is a leading researcher at the intersection of artificial intelligence and reinforcement learning, with a primary focus on enhancing autonomous decision-making systems. His most cited work, the 2024 survey "Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods," has already garnered over 105 citations, establishing him as a key voice in this rapidly evolving field. Yan's major contribution lies in systematically bridging large language models (LLMs) with reinforcement learning (RL), demonstrating how LLMs' extensive pretrained knowledge and high-level reasoning can dramatically improve RL's multitask learning, sample efficiency, and complex task planning. This work provides a foundational taxonomy that has become essential for researchers seeking to integrate language-based cognition into robotic and game-playing agents. Beyond this survey, Yan's research continues to push boundaries in scalable AI systems, making his profile a must-read for students and scholars interested in the future of intelligent, adaptive agents.
Research Focus
Key Achievements
Top Papers
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