3 papers
cs.CV2026
Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models
Sakshi Agarwal, Aishik Konwer, Ankit Parag Shah
Video Anomaly Detection (VAD) has traditionally been framed as binary classification or outlier detection, providing neither interpretable reasoning nor precise spatial localizatio…
q-bio.TO2026
Gaze2Report: Radiology Report Generation via Visual-Gaze Prompt Tuning of LLMs
Aishik Konwer, Moinak Bhattacharya, Prateek Prasanna
Existing deep learning methods for radiology report generation enhance diagnostic efficiency but often overlook physician-informed medical priors. This leads to a suboptimal alignm…
cs.CV2025
Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation
Aishik Konwer, Zhijian Yang, Erhan Bas +4
Foundational models such as the Segment Anything Model (SAM) are gaining traction in medical imaging segmentation, supporting multiple downstream tasks. However, such models are su…