Papers with full-resource and low-resource settings
Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding (2022.emnlp-main)
Copied to clipboard
| Challenge: | Existing knowledge-enhanced pre-trained language models (PLMs) introduce redundant factual knowledge from knowledge bases and require complex modules. |
| Approach: | They propose a knowledge prompting-based PLM framework that incorporates factual knowledge into PLMs. |
| Outcome: | The proposed framework can be flexibly combined with existing mainstream PLMs. |
Know-Adapter: Towards Knowledge-Aware Parameter-Efficient Transfer Learning for Few-shot Named Entity Recognition (2024.lrec-main)
Copied to clipboard
| Challenge: | Named entity recognition (NER) is a fundamental task in natural language processing. |
| Approach: | They propose a knowledgeable adapter to incorporate structure and semantic knowledge of knowledge graphs into PLMs for few-shot NER. |
| Outcome: | The proposed adapter improves the quality of retrieved information by adding explicit knowledge from external sources to PEFTs. |