15 papers
People-Centred Medical Image Analysis via Fairness-Aware Human-AI Cooperation
Zheng Zhang, Milad Masroor, Cuong Nguyen +6
Machine learning models for medical image analysis often exhibit subgroup-dependent performance, which impacts how decisions should be allocated between automated systems and human…
Fairness Beyond Demographics: Optimizing Performance Across Appearance-Based Hidden Cohorts in Medical Imaging
Milad Masroor, Cuong Nguyen, Kevin Wells +1
Medical image analysis models can exhibit performance disparities across patient subgroups, threatening clinical safety and fairness. Existing methods typically address this issue…
Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models
Dung Anh Hoang, Cuong Pham, Cuong Nguyen +3
Large Language Models (LLMs) deliver strong performance across a wide range of NLP tasks, but their massive sizes hinder deployment on resource-constrained devices. To reduce their…
Multi-agent decision making: A Blackwell's informativeness approach
Zheng Zhang, Cuong C. Nguyen, Kevin Wells +1
The rapid development of large language models (LLMs) has motivated research on decision-making in multi-agent systems, where multiple agents collaborate to achieve shared objectiv…
Fatigue-Aware Learning to Defer via Constrained Optimisation
Zheng Zhang, Cuong C. Nguyen, David Rosewarne +2
Learning to defer (L2D) enables human-AI cooperation by deciding when an AI system should act autonomously or defer to a human expert. Existing L2D methods, however, assume static…
Adaptive Layer-Wise Transformations for Post-Training Quantization of Large Language Models
Cuong Pham, Hoang Anh Dung, Cuong C. Nguyen +4
Large language models require significant computational resources for deployment, making quantization essential for practical applications. However, the main obstacle to effective…