Papers by David Fraile Navarro
Few-shot fine-tuning SOTA summarization models for medical dialogues (2022.naacl-srw)
Copied to clipboard
| Challenge: | Abstractive summarization of medical dialogues is a challenge for standard training approaches due to the paucity of suitable datasets. |
| Approach: | They propose to use medical dialogues to generate abstractive summaries using transformer-based models with zero-shot and few-shot learning strategies. |
| Outcome: | The proposed models were compared with a medical dialogue dataset with 143 snippets and a general domain and dialogue-specific text to assess their performance. |