Rong Fu

Medical LLMs can achieve superior QA performance by dynamically selecting specialized adaptation components based on question context and clinical tags, surpassing static parameter-efficient methods.

SciLENS outperforms existing models in scientific literature synthesis by leveraging structural visualization to enhance reasoning and context retention.

Gradient-Aligned Reward transforms how we leverage expert knowledge in reinforcement learning, enabling LLMs to achieve superior reasoning performance with minimal overhead.

CM2 achieves unprecedented gains in cultural reasoning for MLLMs, revealing the power of a multi-agent approach to interdisciplinary challenges.