Domain Expertise
Domain expertise in artificial intelligence focuses on enhancing large language models (LLMs) and other AI agents to perform specialized tasks effectively. Current research emphasizes methods for integrating domain-specific knowledge, often through techniques like fine-tuning with curated datasets, knowledge graph augmentation, and multi-agent systems that combine the strengths of different specialized models. This work aims to improve the accuracy, efficiency, and cost-effectiveness of AI systems across various fields, from medicine and law to scientific research and engineering, by bridging the gap between general-purpose AI and task-specific performance. The resulting advancements have significant implications for both scientific discovery and practical applications requiring high levels of accuracy and reliability.
Papers
A Critical Review of Large Language Models: Sensitivity, Bias, and the Path Toward Specialized AI
Arash Hajikhani, Carolyn Cole
TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety
Ou Zheng, Mohamed Abdel-Aty, Dongdong Wang, Chenzhu Wang, Shengxuan Ding