collaborators

7 papers

cs.AI2026

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…

cs.LG2026

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…

cs.CV2026

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…

cs.LG2026

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…

cs.CL2026

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.…

cs.CV2026

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…