Weighting What Matters: Boosting Sample Efficiency in Medical Report Generation via Token Reweighting

This work introduces a token reweighting loss function to enhance data efficiency in training vision-language models for medical report generation. By prioritizing semantically salient tokens, the method achieves comparable report quality using up to ten times less training data.