Local Evidence, Global Rule: When Knowledge Graph Embeddings Generalize Too Far
TL;DR for operators A knowledge graph may observe the same relational pattern only a handful of times and still use an embedding model whose architecture effectively treats that pattern as valid everywhere. That is not merely a sparse-data problem. It is a generalization-control problem. Kim and Kim call this failure pattern over-generalization and propose PogRE, a knowledge graph embedding architecture designed to make a pattern’s reach expand as supporting evidence covers more independent directions in embedding space.1 The paper reports both competitive link-prediction results and lower targeted over-generalization measurements than TransE, RotatE, PairRE, and CompoundE in the evaluated settings. ...
