Category:
Category:
Category:
Model Training & Tuning
Definition
Adapting a general LLM to perform well in a specific industry or task domain.
Explanation
Domain adaptation fine-tunes or augments LLMs using domain-specific text, terminology, structures, and workflows. It increases accuracy, contextual awareness, and compliance. Methods include supervised fine-tuning, synthetic data generation, RAG augmentation, or adapter-based specialization.
Technical Architecture
Base Model → Domain Dataset → Adaptation/Tuning → Evaluation → Deployment
Core Component
Domain corpus, labeling, validation benchmarks, tuning pipeline
Use Cases
Healthcare QA, legal assistants, telco copilots, finance copilots
Pitfalls
Dataset bias, catastrophic forgetting, domain drift
LLM Keywords
Domain Adaptation, Domain Tuned LLM, Specialized LLM
Related Concepts
Related Frameworks
• Fine-Tuning
• Synthetic Data
• Retrieval Pipelines
• Domain Adaptation Workflow