ShuLiang Zhao

2 accepted papers

2026

ALEX:A Light Editing-knowledge Extractor

Minghu Wang, ShuLiang Zhao, Yuanyuan Zhao, Hongxia Xu

AAAI 2026technical

The static nature of knowledge within Large Language Models (LLMs) makes it difficult for them to adapt to evolving information, rendering knowledge editing a critical task. However, existing methods struggle with challenges of scalability and retrieval efficiency, particularly when handling complex

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2025

STF: Spatio-Temporal Fusion-Based Multi-Agent Path-Finding

Shuliang Zhao, Yanmei Yu, Qingchuan Tao

RA-L 2025

Multi-agent pathfinding (MAPF) plays a critical role in tasks involving collaborative multi-agent systems, particularly in complex environments, where it ensures the safe navigation of each agent while avoiding conflicts. However, existing methods still face numerous challenges, especially in high-d

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