24 citations · 91 across the 37 of their papers we have counts for
8 papers · 1 filter
Secure and Explainable Fraud Detection in Finance via Hierarchical Multi-source Dataset Distillation
Yiming Qian, Thorsten Neumann, Xueyining Huang +4
We propose an explainable, privacy-preserving dataset distillation framework for collaborative financial fraud detection. A trained random forest is converted into transparent, axi…
EVLF-FM: Explainable Vision Language Foundation Model for Medicine
Yang Bai, Haoran Cheng, Yang Zhou +40
Despite the promise of foundation models in medical AI, current systems remain limited - they are modality-specific and lack transparent reasoning processes, hindering clinical ado…
Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Yang Zhou, Chrystie Wan Ning Quek, Jun Zhou +22
Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulte…
AdvMIM: Adversarial Masked Image Modeling for Semi-Supervised Medical Image Segmentation
Lei Zhu, Jun Zhou, Rick Siow Mong Goh +1
Vision Transformer has recently gained tremendous popularity in medical image segmentation task due to its superior capability in capturing long-range dependencies. However, transf…
An integrated language-vision foundation model for conversational diagnostics and triaging in primary eye care
Zhi Da Soh, Yang Bai, Kai Yu +28
Current deep learning models are mostly task specific and lack a user-friendly interface to operate. We present Meta-EyeFM, a multi-function foundation model that integrates a larg…
Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
Lei Zhu, Yanyu Xu, Huazhu Fu +3
Unpaired Multi-Modal Learning (UMML) which leverages unpaired multi-modal data to boost model performance on each individual modality has attracted a lot of research interests in m…
AiRacleX: Automated Detection of Price Oracle Manipulations via LLM-Driven Knowledge Mining and Prompt Generation
Bo Gao, Yuan Wang, Qingsong Wei +3
Decentralized finance (DeFi) applications depend on accurate price oracles to ensure secure transactions, yet these oracles are highly vulnerable to manipulation, enabling attacker…
Look Back for More: Harnessing Historical Sequential Updates for Personalized Federated Adapter Tuning
Danni Peng, Yuan Wang, Huazhu Fu +4
Personalized federated learning (PFL) studies effective model personalization to address the data heterogeneity issue among clients in traditional federated learning (FL). Existing…