activity
20242026
collaborators

5 papers

cs.CV2026

RadJEPA: Radiology Encoder for Chest X-Rays via Joint Embedding Predictive Architecture

Anas Anwarul Haq Khan, Mariam Husain, Pratik Jalan +1

Vision-language pretraining has driven much of the recent progress in medical image representation learning, but this paradigm is constrained by the availability of paired image-te…

cs.CL2025

Broken Words, Broken Performance: Effect of Tokenization on Performance of LLMs

Sachin Pawar, Manoj Apte, Kshitij Jadhav +2

Tokenization is the first step in training any Large Language Model (LLM), where the text is split into a sequence of tokens as per the model's fixed vocabulary. This tokenization…

cs.CV2025

Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification

Raja Kumar, Raghav Singhal, Pranamya Kulkarni +2

Deep multimodal learning has shown remarkable success by leveraging contrastive learning to capture explicit one-to-one relations across modalities. However, real-world data often…

eess.IV2025

Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models

Deval Mehta, Yiwen Jiang, Catherine L Jan +3

Recent advancements in deep learning have shown significant potential for classifying retinal diseases using color fundus images. However, existing works predominantly rely exclusi…

cs.CV2024

IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework

Anurag Shandilya, Swapnil Bhat, Akshat Gautam +4

Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-ta…