collaborators

10 papers

cs.AI2026

TriAlign: Towards Universal Truth Consistency in Personalized LLM Alignment

Thi-Nhung Nguyen, Linhao Luo, Rollin Omari +3

Personalized large language models adapt responses to users' preferences and social attributes, but can introduce substantial universal truth inconsistencies across social groups,…

cs.MA2026

The Social Cost of Intelligence: Emergence, Propagation, and Amplification of Stereotypical Bias in Multi-Agent Systems

Thi-Nhung Nguyen, Linhao Luo, Amardeep Kaur +5

Bias in large language models (LLMs) remains a persistent challenge, often leading to stereotyping and unfair treatment across social groups. While prior work has mainly focused on…

cs.CL2026

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models

Linhao Luo, Thuy-Trang Vu, Van-Anh Nguyen +3

Aligning large language models (LLMs) with diverse and multifaceted user preferences is a fundamental challenge in personalized AI systems. Existing multi-objective alignment metho…

cs.AI2026

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge

Linhao Luo, Zicheng Zhao, Junnan Liu +9

Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented generation (RAG) mitigates this by inc…

cs.CL2026

MCBench: A Multicontext Safety Assessment Benchmark for Omni Large Language Models

Manh Luong, Tamas Abraham, Junae Kim +6

Existing multimodal safety benchmarks focus solely on visual inputs and cannot assess Omni Large Language Models (LLMs) that process vision, audio, and text. We introduce MCBench,…

cs.AI2026

LiveCultureBench: a Multi-Agent, Multi-Cultural Benchmark for Large Language Models in Dynamic Social Simulations

Viet-Thanh Pham, Lizhen Qu, Thuy-Trang Vu +2

Large language models (LLMs) are increasingly deployed as autonomous agents, yet evaluations focus primarily on task success rather than cultural appropriateness or evaluator relia…