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This article discusses BaNEL, a new algorithm that improves generative models by training them using only negative reward samples. It addresses the challenges of reward sparsity and costly evaluations in complex problem-solving scenarios, demonstrating its effectiveness through various experiments.
This article discusses the common reasons why enterprise ontologies and knowledge graphs often fail. The author draws on personal experience with machine learning projects to highlight key issues in design and implementation.