Papers with biomedical natural language processing
Meta-Learning Adaptive Knowledge Distillation for Efficient Biomedical Natural Language Processing (2022.findings-aacl)
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| Challenge: | Existing knowledge distillation methods have been proposed to reduce the size of large models for biomedical natural language processing tasks. |
| Approach: | They propose a meta-learning approach which adaptively learns parameters that enable optimal rate of knowledge exchange between teacher and student models from the distillation data during knowledge distillation. |
| Outcome: | The proposed method improves the performance of knowledge distillation methods on two biomedical natural language processing tasks. |
BioReader: a Retrieval-Enhanced Text-to-Text Transformer for Biomedical Literature (2022.emnlp-main)
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| Challenge: | Recent research has equipped language models with the ability to attend over relevant and factual information from non-parametric external sources, drawing a complementary path to architectural scaling. |
| Approach: | They propose a retrieval-enhanced text-to-text model that augments the input prompt by fetching and assembling relevant scientific literature chunks from a neural database centered on PubMed. |
| Outcome: | The proposed model outperforms state-of-the-art models on a broad array of downstream tasks while using up to 3x fewer parameters. |
Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization (2023.emnlp-main)
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| Challenge: | Existing methods for biomedical named entity recognition require laborious human effort. |
| Approach: | They propose a Synonym Generalization framework that recognizes biomedical concepts using span-based predictions. |
| Outcome: | The proposed framework outperforms dictionary-based approaches on a wide range of benchmarks. |