AINeutralarXiv – CS AI · Jun 26/10
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On the Theoretical Limitations of Embedding-based Link Prediction
Researchers identify fundamental limitations in knowledge graph embedding models caused by linear output layers that create "rank bottlenecks," restricting how well these systems can learn link prediction tasks. The study proposes using non-linear mixture-based output layers as a solution, demonstrating improved performance on large, dense datasets without substantial parameter increases.