7 papers
Robust Lightweight Deep Learning Models for Oral Cancer Screening
Siddhant Bharadwaj, Aakash Shedsale, Tejashree Subramanya +6
Oral cancer is a leading cause of mortality in low-to-middle-income countries, where a shortage of specialists delays diagnosis. While point-of-care screening via smartphones offer…
Do Medical Vision Language Models Actually See? A Counterfactual Grounding Framework and Hard-Negative Contrastive Training for Visually-Reliant Medical VLMs
Anas Zafar, Leema Krishna Murali, Siddhant Bharadwaj +2
Large vision language models (VLMs) report strong accuracy on medical question-answering, yet it remains unclear whether they reason from visual evidence or exploit textual shortcu…
Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks
Benjamin Warner, Ratna Sagari Grandhi, Max Kieffer +32
Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insufficient coverage of relevant…
Where Do Vision-Language Models Fail? World Scale Analysis for Image Geolocalization
Siddhant Bharadwaj, Ashish Vashist, Fahimul Aleem +1
Image geolocalization has traditionally been addressed through retrieval-based place recognition or geometry-based visual localization pipelines. Recent advances in Vision-Language…
Spatial Reasoning is Not a Free Lunch: A Controlled Study on LLaVA
Nahid Alam, Leema Krishna Murali, Siddhant Bharadwaj +7
Vision-language models (VLMs) have advanced rapidly, yet they still struggle with basic spatial reasoning. Despite strong performance on general benchmarks, modern VLMs remain brit…
The Spatial Blindspot of Vision-Language Models
Nahid Alam, Leema Krishna Murali, Siddhant Bharadwaj +7
Vision-language models (VLMs) have advanced rapidly, but their ability to capture spatial relationships remains a blindspot. Current VLMs are typically built with contrastive langu…