9 papers
Humans Are More Diverse: Frontier LLMs Show Extreme Policies in Idealised AI Development Races
Phu Hoa Pham, Duy Minh Dao Sy, Trung Kiet Huynh +9
An AI development race creates a multi-agent safety dilemma. Each company can develop slowly and safely, or move faster while taking a risk that may remove its final reward. We use…
Unlocking Compositional Generalization in Continual Few-Shot Learning
Phu-Quy Nguyen-Lam, Phu-Hoa Pham, Dao Sy Duy Minh +3
Object-centric representations promise a key property for few-shot learning: Rather than treating a scene as a single unit, a model can decompose it into individual object-level pa…
Weather-Robust Cross-View Geo-Localization via Prototype-Based Semantic Part Discovery
Chi-Nguyen Tran, Dao Sy Duy Minh, Huynh Trung Kiet +3
Cross-view geo-localization (CVGL), which matches an oblique drone view to a geo-referenced satellite tile, has emerged as a key alternative for autonomous drone navigation when GN…
MIST: Reliable Streaming Decision Trees for Online Class-Incremental Learning via McDiarmid Bound
Phu-Hoa Pham, Chi-Nguyen Tran, Nguyen Lam Phu Quy +3
Streaming decision trees are natural candidates for open-world continual learning, as they perform local updates, enjoy bounded memory, and static decision boundaries. Despite thes…
Training-Free Cultural Alignment of Large Language Models via Persona Disagreement
Huynh Trung Kiet, Dao Sy Duy Minh, Tuan Nguyen +5
Large language models increasingly mediate decisions that turn on moral judgement, yet a growing body of evidence shows that their implicit preferences are not culturally neutral.…
Navigating Simply, Aligning Deeply: Winning Solutions for Mouse vs. AI 2025
Phu-Hoa Pham, Chi-Nguyen Tran, Dao Sy Duy Minh +2
Visual robustness and neural alignment remain critical challenges in developing artificial agents that can match biological vision systems. We present the winning approaches from T…