Papers with knowledge embedding model
Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model (D19-1)
Copied to clipboard
| Challenge: | Entity alignment aims at integrating complementary knowledge graphs (KGs) from different sources or languages. |
| Approach: | They propose a semi-supervised entity alignment method by joint Knowledge Embedding model and Cross-Graph model to make better use of seed alignments to propagate over the entire graphs with KG-based constraints. |
| Outcome: | The proposed method can make better use of seed alignments to propagate over entire graphs with KG-based constraints. |
Generic Overgeneralization in Pre-trained Language Models (2022.coling-1)
Copied to clipboard
| Challenge: | Generic statements such as "ducks lay eggs" are perceived as false universally . however, universally quantified statements such "all tigers have stripes" should be perceived as true . |
| Approach: | They investigate the generic overgeneralization effect in pre-trained language models . they show that pre-trainers tend to treat quantified generic statements as if they were true . |
| Outcome: | The proposed model reduces, but does not eliminate, generic overgeneralization bias . the model can be used to inject factual knowledge about kinds into pre-trained models . |