3 citations · 3 across the 3 of their papers we have counts for
6 papers
Trustworthy Medical Imaging with Large Language Models: A Study of Hallucinations Across Modalities
Anindya Bijoy Das, Shahnewaz Karim Sakib, Shibbir Ahmed
Large Language Models (LLMs) are increasingly applied to medical imaging tasks, including image interpretation and synthetic image generation. However, these models often produce h…
Can Large Language Models Challenge CNNs in Medical Image Analysis?
Shibbir Ahmed, Shahnewaz Karim Sakib, Anindya Bijoy Das
This study presents a multimodal AI framework designed for precisely classifying medical diagnostic images. Utilizing publicly available datasets, the proposed system compares the…
Multi-Agent Reinforcement Learning for Graph Discovery in D2D-Enabled Federated Learning
Satyavrat Wagle, Anindya Bijoy Das, David J. Love +1
Augmenting federated learning (FL) with device-to-device (D2D) communications can help improve convergence speed and reduce model bias through local information exchange. However,…
Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models
Anindya Bijoy Das, Shibbir Ahmed, Shahnewaz Karim Sakib
Clinical summarization is crucial in healthcare as it distills complex medical data into digestible information, enhancing patient understanding and care management. Large language…
Learning-Based Two-Way Communications: Algorithmic Framework and Comparative Analysis
David R. Nickel, Anindya Bijoy Das, David J. Love +1
Machine learning (ML)-based feedback channel coding has garnered significant research interest in the past few years. However, there has been limited research exploring ML approach…
Battling Misinformation: An Empirical Study on Adversarial Factuality in Open-Source Large Language Models
Shahnewaz Karim Sakib, Anindya Bijoy Das, Shibbir Ahmed
Adversarial factuality refers to the deliberate insertion of misinformation into input prompts by an adversary, characterized by varying levels of expressed confidence. In this stu…