Research Index

A novel framework that dynamically allocates computational resources during LLM reasoning based on task complexity and required accuracy. By combining insights from token entropy patterns and length-controlled reasoning, the system adaptively switches between short and long-form reasoning to optimize performance while minimizing computational costs.

A novel framework combining ThinkPrune's reasoning optimization with HealthBench's medical evaluation metrics to create resource-efficient medical LLMs for clinical deployment. The system dynamically adjusts reasoning depth based on task complexity and available computational resources while maintaining safety through biomedical knowledge graph verification.