Basit Alawode — accepted AI-conference papers

2026

MLLM-HWSI: A Multimodal Large Language Model for Hierarchical Whole Slide Image Understanding

Basit Alawode, Arif Mahmood, Muaz Khalifa Al Radi, Shahad Albastaki, Asim Khan, Muhammad Bilal +3

CVPR 2026

Whole Slide Images (WSIs) exhibit hierarchical structure, where diagnostic information emerges from cellular morphology, regional tissue organization, and global context. Existing Computational Pathology (CPath) Multimodal Large Language Models (MLLMs) typically compress an entire WSI into a single

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2025

Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representation

Shahad Albastaki, Anabia Sohail, Iyyakutti Iyappan Ganapathi, Basit Alawode, Asim Khan, Sajid Javed +3

CVPR 2025poster

In Computational Pathology (CPath), the introduction of Vision-Language Models (VLMs) has opened new avenues for research, focusing primarily on aligning image-text pairs at a single magnification level. However, this approach might not be sufficient for tasks like cancer subtype classification, tis…

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