Constructing and Evaluating Clinical Reasoning Trajectories for Medical Agent
MedTraj is proposed, a framework that treats reasoning trajectories as critical objects for construction, evaluation, and optimization, and quality-weighted context learning feeds trajectory evaluations back into the model at inference time, allowing it to learn from both strong and weak reasoning demonstrations.