Papers by Breno William Carvalho

1 papers
Logical Neural Networks for Knowledge Base Completion with Embeddings & Rules (2022.emnlp-main)

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Challenge: Knowledge base completion (KBC) is a human-interpretable dialect . rule-based KBC has a high quality but low accuracy .
Approach: They propose to use logical neural networks to learn both kinds of rules in a common framework using gradient-based optimization.
Outcome: The proposed method improves by 10% relative to SotA rule-based methods and by combining it with knowledge graph embeddings it achieves an additional 7.5% relative improvement.

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