6 papers
Bridging Thought and Action: Taming Long-Horizon Instability in Open-Source LLM Agents with a MetaTool-Enhanced ROS Framework
Kazi Abrar Mahmud, Nilotpaul Kundu Dhurubo, Tamal Kirttonia +2
Large Language Models (LLMs) have enabled more natural human-robot interaction, but open-source models often exhibit unstable long-horizon reasoning and inefficient action executio…
Skip What You Can Predict: Predictive Repositioning for Policy Optimization for Efficient LLM Training
Ismam Nur Swapnil, Aranya Saha, Tanvir Ahmed Khan +3
Reinforcement learning with verifiable rewards (RLVR) can improve the reasoning ability of large language models, but repeatedly updating a policy on the same rollout batch is expe…
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…
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…
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…
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 But they face challenges such as hallucination and outdated knowledge.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…