collaborators

5 papers

cs.LG2026

Gradient Extrapolation-Based Policy Optimization

Ismam Nur Swapnil, Aranya Saha, Tanvir Ahmed Khan +2

Reinforcement learning is widely used to improve the reasoning ability of large language models, especially when answers can be automatically checked. Standard GRPO-style training…

cs.CL2025

GRPO++: Enhancing Dermatological Reasoning under Low Resource Settings

Ismam Nur Swapnil, Aranya Saha, Tanvir Ahmed Khan +1

Vision-Language Models (VLMs) show promise in medical image analysis, yet their capacity for structured reasoning in complex domains like dermatology is often limited by data scarc…

cs.AI2025

Compression Strategies for Efficient Multimodal LLMs in Medical Contexts

Tanvir A. Khan, Aranya Saha, Ismam N. Swapnil +1

Multimodal Large Language Models (MLLMs) hold huge potential for usage in the medical domain, but their computational costs necessitate efficient compression techniques. This paper…

cs.CV2025

CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering

Aranya Saha, Tanvir Ahmed Khan, Ismam Nur Swapnil +1

Vision-language models (VLMs) have shown significant potential for medical tasks; however, their general-purpose nature can limit specialized diagnostic accuracy, and their large s…

cs.CL2025

LLM-Assisted Question-Answering on Technical Documents Using Structured Data-Aware Retrieval Augmented Generation

Shadman Sobhan, Mohammad Ariful Haque

Large Language Models (LLMs) are capable of natural language understanding and generation. But they face challenges such as hallucination and outdated knowledge. Fine-tuning is one…