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cs.AI2026
Brain-Inspired Graph Multi-Agent Systems for LLM Reasoning
Guangfu Hao, Yuming Dai, Xianzhe Qin +1
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of language tasks, yet complex multi-step reasoning remains a fundamental challenge. Whil…
cs.AI2025
Agentic Lybic: Multi-Agent Execution System with Tiered Reasoning and Orchestration
Liangxuan Guo, Bin Zhu, Qingqian Tao +5
Autonomous agents for desktop automation struggle with complex multi-step tasks due to poor coordination and inadequate quality control. We introduce Agentic Lybic, a novel multi-a…
cs.AI2025
Visual Large Language Models Exhibit Human-Level Cognitive Flexibility in the Wisconsin Card Sorting Test
Guangfu Hao, Frederic Alexandre, Shan Yu
Cognitive flexibility has been extensively studied in human cognition but remains relatively unexplored in the context of Visual Large Language Models (VLLMs). This study assesses…