Papers by Ka-Chun Wong
EARA: Improving Biomedical Semantic Textual Similarity with Entity-Aligned Attention and Retrieval Augmentation (2023.findings-emnlp)
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| Challenge: | Existing methods to measure semantic similarity between biomedical texts are inefficient due to too many biomedically-related entities. |
| Approach: | They propose an entity-aligned, attention-based and retrieval-augmented PLM that aligns the same type of fine-grained entity information in each sentence pair with an entity alignment matrix with an auxiliary loss. |
| Outcome: | The proposed model can achieve state-of-the-art on both in-domain and out-of domain datasets. |