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A-CONECT: Designing AI-based Conversational Chatbot for Early Dementia Intervention

We develop a chatbot for early dementia prevention and leverage LLMs to build digital twins to evaluate chatbots.

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Zeroth-order optimization for LLM.

A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection

We develop a hybrid federated learning for learning financial-crime predictive models from horizontal and vertical federated data structures.

FedNoisy: A Federated Noisy Label Learning Benchmark

The recent decade witnessed a surge of increase in financial crimes across the public and private sectors, with an average cost of scams of $102m to financial institutions in 2022. Developing a mechanism for battling financial crimes is an impending …

Precautionary Unfairness in Self-Supervised Contrastive Pre-training

Recently, self-supervised contrastive pre-training has become the de facto regime, that allows for efficient downstream fine-tuning. Meanwhile, its fairness issues are barely studied, though they have drawn great attention from the machine learning …