Small Language Model Agents Enable Efficient and High-Quality Knowledge Mining
Researchers have developed Falconer, a framework designed to make knowledge mining more efficient and cost-effective. This system combines the reasoning capabilities of large language models (LLMs) with smaller, specialized proxy models. LLMs in Falconer act as planners to break down user instructions and as annotators to train the proxy models. This approach significantly reduces inference costs and speeds up large-scale knowledge extraction compared to using LLMs alone. AI
IMPACT This framework could significantly reduce the cost and increase the speed of knowledge extraction for AI applications.