15 papers
Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
Yuyuan Feng, Zhishang Xiang, Chaobin Yang +32
LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms including Prompt Engineering to elicit…
EASy: Towards Efficient LLM-Based Agentic System
Junnan Liu, Linhao Luo, Thuy-Trang Vu +1
Agentic systems have emerged as a promising paradigm for solving complex tasks by coordinating specialized LLM-based agents. However, most existing systems primarily optimize task…
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,…
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…
Toward Native Multimodal Modeling: A Roadmap
Siyu An, Junru Lu, Junnan Dong +18
Multimodal modeling represents a vital step from modality-agnostic reasoning toward world modeling. While early approaches predominantly rely on late-fusion that assembles encoders…
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…