National Natural Science Foundation of China [61402220]; Philosophy and Social Science Foundation of Hunan Province [16YBA323]; Natural Science Foundation of Hunan Province [2020JJ4525,2022JJ30495]; Scientific Research Fund of Hunan Provincial Education Department [18B279,19A439,22A0316]
机构署名：
本校为第一且通讯机构
摘要：
The task of Knowledge Graph Completion (KGC) entails inferring missing relations and facts in a partially specified graph to discover new knowledge. However, the discrepancy in the targets between the training and inference phases might lead to in-depth bias and in-breadth bias during inference, potentially resulting in incorrect outcomes. In this work, we conduct a comprehensive analysis of these biases to determine their extent of impact. To mitigate these biases, we propose a novel debiasing framework called Causal Inference-based Debiasing Framework for KGC (CIDF) by formulating a causal g...
