Category:
Category:
Knowledge Distillation for Agents
Category:
Model Optimization
Definition
Teaching smaller agents or models to mimic more advanced ones.
Explanation
Knowledge distillation transfers reasoning and behavior patterns from a large 'teacher' agent or LLM to a smaller 'student' model or agent. This improves efficiency and reduces cost while preserving performance. It is especially useful for specialized agents performing narrow tasks.
Technical Architecture
Teacher Agent → Distillation Dataset → Student Agent → Evaluation
Core Component
Teacher agent, student agent, dataset generator, evaluator
Use Cases
Agent optimization, edge AI, cost reduction, multi-agent workflows
Pitfalls
Student models lose depth; require high-quality distillation datasets
LLM Keywords
Agent Distillation, Student Agent, Knowledge Transfer
Related Concepts
Related Frameworks
• Model Distillation
• Compression
• Routing
• Agent Distillation Pipeline