Papers with deep empirical analysis
Great~Truths~are ~Always ~Simple: A Rather Simple Knowledge Encoder for Enhancing the Commonsense Reasoning Capacity of Pre-Trained Models (2022.findings-naacl)
Copied to clipboard
| Challenge: | Existing approaches to enhance pre-trained language models (PTMs) with a knowledge-aware graph neural network (GNN) encoder that models a commonsense knowledge graph (CSKG) can't explain how external knowledge resources improve the reasoning capacity of PTMs. |
| Approach: | They propose to use relation features from CSKGs to enhance the reasoning capacity of pre-trained language models (PTMs) by encoding a commonsense knowledge graph (CSKG) |
| Outcome: | The proposed approach reduces the parameters for encoding CSKGs and improves on five benchmarks. |