Search, Do not Guess: Teaching Small Language Models to Be Effective Search Agents

1. 1Identify the limitations of Large Language Models (LLMs) in terms of computational cost
2. 2Distill agentic behaviors from LLMs into Small Language Models (SLMs)
3. 3Evaluate the performance of SLMs on complex multi-hop reasoning tasks
4. 4Fine-tune SLMs to improve their search capabilities

AI researchers and engineers can benefit from this research as it enables the development of more efficient and effective search agents, while product managers can apply these findings to improve search functionality in their products

💡 Small Language Models can be taught to be effective search agents, reducing the need for computationally expensive Large Language Models

💡 Small Language Models can be effective search agents with the right training #AI #LLMs