Papers with KBC

3 papers
Reasoning Over Paths via Knowledge Base Completion (D19-53)

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Challenge: Existing methods to predict missing links in knowledge graphs are lacking.
Approach: They propose a method to automatically rank paths between a source and target entity pair using a knowledge base completion model.
Outcome: The proposed method can rank and rank paths in biomedical knowledge graphs with a KBC model.
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.
Joint Knowledge Base Completion and Question Answering by Combining Large Language Models and Small Language Models (2026.acl-long)

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Challenge: Existing studies rely on the small language model (SLM) to enhance them jointly, and the large language model’s strong reasoning ability is ignored.
Approach: They propose a framework which can make knowledge base completion and knowledge base question answering enhance each other in an iterative manner by combining the strengths of the small language model and the large language model.
Outcome: The proposed framework surpasses baselines for both KBC and KBQA tasks over two public benchmark data sets.

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