3 citations · 5 across the 9 of their papers we have counts for
9 papers
Memory as an Attack Surface in LLM Agents: A Study on Multiple-Choice Question Answering
Shahnewaz Karim Sakib, Anindya Bijoy Das
AI agents extend conventional large language model (LLM) applications by integrating language understanding with task execution, external tool use, and memory mechanisms. While mem…
Preventing Error Propagation in Multi-Agent AI through Runtime Monitoring
Shahnewaz Karim Sakib, Anindya Bijoy Das
Multi-agent AI systems can improve answer selection by allowing different language models to exchange reasoning traces, revise initial predictions, and support a final decision. Ho…
Adversarial Reframing: A Framework for Targeted Generation in Language Models
Shahnewaz Karim Sakib, Swati Kar, Anindya Bijoy Das
Large Language Models (LLMs) are widely deployed in diverse real-world settings, yet remain vulnerable to jailbreaking, where prompt-based attacks bypass safety filters. We present…
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…
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…
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…
Fighter Jet Navigation and Combat using Deep Reinforcement Learning with Explainable AI
Swati Kar, Soumyabrata Dey, Mahesh K Banavar +1
This paper presents the development of an Artificial Intelligence (AI) based fighter jet agent within a customized Pygame simulation environment, designed to solve multi-objective…
Unveiling and Mitigating Bias in Large Language Model Recommendations: A Path to Fairness
Anindya Bijoy Das, Shahnewaz Karim Sakib
Large Language Model (LLM)-based recommendation systems excel in delivering comprehensive suggestions by deeply analyzing content and user behavior. However, they often inherit bia…