arXiv Computer Vision
PLRS-IC: A Dual-Calibration Framework for Chest X-Ray Vision-Language Alignment
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CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement
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AlphaRAD: Grounded Zero-Shot Classification in Chest Radiology via $\alpha$-Corrected Binary Cross Entropy and Factorized Latent Supervision
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GLINT: Sparsely Gated Vision-Language Alignment for Fine-Grained Radiology Representations
arXiv:2606. 03180v1 Announce Type: cross Abstract: Vision-language models (VLMs) for radiology have emerged as a scalable paradigm by leveraging image-report pairs naturally produced in clinical workflows.
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EndoVLM: An Endoscopy Vision-Language Pre-training Model via Anatomy-Guided Sparsity and Progressive Alignment
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RadPRISM: Schema-stratified radiology-report supervision for concept-disentangled image representations and visual grounding
arXiv:2608. 00147v1 Announce Type: cross Abstract: Vision-language pretraining learns rich medical image representations from radiology reports, but previous model variants commonly operate within a single shared embedding space, so concept-level structure and interpretability must be recovered post hoc, limiting model transparency and, hence, clinical utility.
arXiv Computation and Language
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Towards Clinically Faithful Medical Image Captioning via Enhanced Vision-Language Alignment
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