8 papers
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…
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…
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…