Recent advances in generative models have highlighted the need for robust
detectors capable of distinguishing real images from AI-generated images. While
existing methods perform well on known generators, their performance often
declines when teste... read more
Deep neural networks (DNNs) and generative AI (GenAI) are increasingly
vulnerable to backdoor attacks, where adversaries embed triggers into inputs to
cause models to misclassify or misinterpret target labels. Beyond traditional
single-trigger scen... read more
We consider the problem of persistent client dropout in asynchronous
Decentralized Federated Learning (DFL). Asynchronicity and decentralization
obfuscate information about model updates among federation peers, making
recovery from a client dropout... read more
Image geolocalization, the task of identifying the geographic location
depicted in an image, is important for applications in crisis response, digital
forensics, and location-based intelligence. While recent advances in large
language models (LLMs)... read more
The preoperative planning of liver surgery relies on Couinaud segmentation
from computed tomography (CT) images, to reduce the risk of bleeding and guide
the resection procedure. Using 3D point-based representations, rather than
voxelizing the CT v... read more
Fine-tuning open-source Vision-Language Models (VLMs) creates a critical yet
underexplored attack surface: vulnerabilities in the base VLM could be retained
in fine-tuned variants, rendering them susceptible to transferable jailbreak
attacks. To de... read more
Raman spectroscopy is an enticing tool for the rapid identification of pathogenic bacteria and has the potential to meet the demand for early diagnosis and timely treatment of patients. However, it remains a challenge to devise a reliable Raman detec... read more
Clinicians usually combine information from multiple sources to achieve the
most accurate diagnosis, and this has sparked increasing interest in leveraging
multimodal deep learning for diagnosis. However, in real clinical scenarios,
due to differen... read more
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific... read more
All-day smart glasses are likely to emerge as platforms capable of continuous
contextual sensing, uniquely positioning them for unprecedented assistance in
our daily lives. Integrating the multi-modal AI agents required for human
memory enhancement... read more
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