A new multi-frame VQA benchmark on volumetric MRI demonstrates that bounding-box supervised fine-tuning improves spatial grounding in VLMs over zero-shot baselines.
Minigpt-med: Large language model as a general interface for radiology diagnosis.arXiv preprint arXiv:2407.04106
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
ESC-RL improves RL for radiology reports via group-wise evidence-aware rewards (GEAR) and LLM-driven self-correcting preference learning (SPL), reaching state-of-the-art on two chest X-ray datasets.
CogAlign uses hierarchical supervised fine-tuning on clinical cognition data plus counterfactual RL to align MLLMs with expert diagnostic pathways and enforce causal lesion grounding for GI endoscopy diagnosis.
citing papers explorer
No citing papers match the current filters.