10 papers
SoK: Rethinking Jailbreaking in the Era of Agentic AI: Attacks, Defenses, and Practical Consideration
Md Jueal Mia, Yanzhao Wu, Selcuk Uluagac +1
Large language models (LLMs) are rapidly evolving from conversational assistants into agentic AI systems that reason, plan, invoke tools, maintain persistent memory, communicate wi…
Don't Overthink, Don't Underthink: Toward Adaptive Reasoning in Agentic AI
Md Jueal Mia, M. Hadi Amini
Recent advances in Large Language Models (LLMs) have shown that increased inference-time reasoning can improve performance on complex tasks. However, many existing approaches rely…
GUARD-SLM: Token Activation-Based Defense Against Jailbreak Attacks for Small Language Models
Md Jueal Mia, Joaquin Molto, Yanzhao Wu +1
Small Language Models (SLMs) are emerging as efficient and economically viable alternatives to Large Language Models (LLMs), offering competitive performance with significantly low…
Jailbreaking Large Vision Language Models in Intelligent Transportation Systems
Badhan Chandra Das, Md Tasnim Jawad, Md Jueal Mia +2
Large Vision Language Models (LVLMs) demonstrate strong capabilities in multimodal reasoning and many real-world applications, such as visual question answering. However, LVLMs are…
JaiLIP: Jailbreaking Vision-Language Models via Loss Guided Image Perturbation
Md Jueal Mia, M. Hadi Amini
Vision-Language Models (VLMs) have remarkable abilities in generating multimodal reasoning tasks. However, potential misuse or safety alignment concerns of VLMs have increased sign…
An Empirical Analysis of Secure Federated Learning for Autonomous Vehicle Applications
Md Jueal Mia, M. Hadi Amini
Federated Learning lends itself as a promising paradigm in enabling distributed learning for autonomous vehicles applications and ensuring data privacy while enhancing and refining…
FedShield-LLM: A Secure and Scalable Federated Fine-Tuned Large Language Model
Md Jueal Mia, M. Hadi Amini
Federated Learning (FL) offers a decentralized framework for training and fine-tuning Large Language Models (LLMs) by leveraging computational resources across organizations while…
Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions
Hadi Amini, Md Jueal Mia, Yasaman Saadati +6
Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as tex…
QuanCrypt-FL: Quantized Homomorphic Encryption with Pruning for Secure Federated Learning
Md Jueal Mia, M. Hadi Amini
Federated Learning has emerged as a leading approach for decentralized machine learning, enabling multiple clients to collaboratively train a shared model without exchanging privat…
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness
Hojat Allah Salehi, Md Jueal Mia, S. Sandeep Pradhan +2
Federated learning (FL) has emerged as a promising framework for distributed machine learning. It enables collaborative learning among multiple clients, utilizing distributed data…