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…
Payoff scaling shapes cooperation in LLM agents across languages
Trung-Kiet Huynh, Dao-Sy Duy-Minh, Thanh-Bang Cao +13
Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users. Whether they cooperate in such settings is no lo…
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.…