Extensive experiments demonstrate that AgentsKG outperforms state-of-the-art training-free baselines in both extraction accuracy and structural quality, offering a robust approach to open-domain knowledge graph construction without additional training.
Shi-Long Liu, Yongqiang Liu, Jiye Liu et al.· Proceedings of the 32nd ACM...· 0 citations
The main result is an explicit optimal embedding of cluster graphs on $n$ vertices, which is strongly NP-complete and admits no FPTAS, while the farthest alignment is polynomial-time solvable.
Jiye Liu, Wenkai Wang, Qiang Tian et al.· 0 citations
Extensive experiments demonstrate that AgentsKG outperforms state-of-the-art training-free baselines in both extraction accuracy and structural quality, offering a robust approach to open-domain knowledge graph construction without additional training.
Shilong Liu, Yongqiang Liu, Jiye Liu et al.· Proceedings of the 32nd ACM...· 0 citations
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