7 citations · 13 across the 12 of their papers we have counts for
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cs.AI2026
BioLLMAgent: A Hybrid Framework with Enhanced Structural Interpretability for Simulating Human Decision-Making in Computational Psychiatry
Zuo Fei, Kezhi Wang, Xiaomin Chen +1
Computational psychiatry faces a fundamental trade-off: traditional reinforcement learning (RL) models offer interpretability but lack behavioral realism, while large language mode…
cs.AI2026
Agentic AI Empowered Intent-Based Networking for 6G
Genze Jiang, Kezhi Wang, Xiaomin Chen +1
The transition towards sixth-generation (6G) wireless networks necessitates autonomous orchestration mechanisms capable of translating high-level operational intents into executabl…
cs.AI2024
Efficient Driving Behavior Narration and Reasoning on Edge Device Using Large Language Models
Yizhou Huang, Yihua Cheng, Kezhi Wang
Deep learning architectures with powerful reasoning capabilities have driven significant advancements in autonomous driving technology. Large language models (LLMs) applied in this…