This research explores techniques to adapt large language models for specialized domains, addressing the limitations of static, general-purpose LLMs.

• Domain-specific adaptation enables LLMs to excel in specialized fields like healthcare and finance
• Dynamic adaptation techniques allow models to evolve beyond their initial training
• Task-adaptive approaches optimize performance for specific applications
• Personalization methods tailor responses to individual or organizational needs

Medical Impact: In healthcare, adapted LLMs can better understand medical terminology, follow clinical guidelines, and provide more accurate information while maintaining patient privacy standards—potentially transforming medical documentation, research, and patient care.

Adaptation of Large Language Models