1 citations · 1 across the 1 of their papers we have counts for
6 papers
Sim-CLIP: Unsupervised Siamese Adversarial Fine-Tuning for Robust and Semantically-Rich Vision-Language Models
Md Zarif Hossain, Ahmed Imteaj
Vision-Language Models (VLMs) rely heavily on pretrained vision encoders to support downstream tasks such as image captioning, visual question answering, and zero-shot classificati…
Adaptive and Robust Data Poisoning Detection and Sanitization in Wearable IoT Systems using Large Language Models
W. K. M Mithsara, Ning Yang, Ahmed Imteaj +2
The widespread integration of wearable sensing devices in Internet of Things (IoT) ecosystems, particularly in healthcare, smart homes, and industrial applications, has required ro…
Digital Forensic Investigation of the ChatGPT Windows Application
Malithi Wanniarachchi Kankanamge, Nick McKenna, Santiago Carmona +3
The ChatGPT Windows application offers better user interaction in the Windows operating system (OS) by enhancing productivity and streamlining the workflow of ChatGPT's utilization…
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…
Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attacks
Mohd. Farhan Israk Soumik, W. K. M. Mithsara, Abdur R. Shahid +1
The rapid proliferation of speech-enabled technologies, including virtual assistants, video conferencing platforms, and wearable devices, has raised significant privacy concerns, p…
TriplePlay: Enhancing Federated Learning with CLIP for Non-IID Data and Resource Efficiency
Ahmed Imteaj, Md Zarif Hossain, Saika Zaman +1
The rapid advancement and increasing complexity of pretrained models, exemplified by CLIP, offer significant opportunities as well as challenges for Federated Learning (FL), a crit…