3 accepted papers
Knowledge distillation has been proven to be an effective method for enhancing model performance, particularly in the domain of model compression. In this study, we propose a comprehensive approach that utilizes Brownian Distance Covariance (BDC) to measure the discrepancy between the logits produce…
Report generation (RG) faces challenges in understanding complex medical images and establishing cross-modal semantic alignment in radiology image-report pairs. Previous methods often overlook fine-grained cross-modal interaction, leading to insufficient understanding of detailed information. Recent…
Multimodal large language models (MLLMs) have demonstrated strong language understanding and generation capabilities, excelling in visual tasks like referring and grounding. However, due to task type limitations and dataset scarcity, existing MLLMs only ground objects present in images and cannot re…