Papers with pre-trained embedding
Employing Glyphic Information for Chinese Event Extraction with Vision-Language Model (2024.findings-emnlp)
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| Challenge: | Recent studies on event extraction have incorporated a variety of features, including textual elements and annotations. |
| Approach: | They propose a glyphic multi-modal Chinese event extraction model with hieroglyphic images to capture morphological structure from the sequence. |
| Outcome: | The proposed model can extract events from a Chinese and KBP Eval datasets at low cost. |
Few-Shot Representation Learning for Out-Of-Vocabulary Words (P19-1)
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| Challenge: | Existing methods for learning word embedding assume there are enough occurrences for each word in the corpus to accurately estimate the representation of words. |
| Approach: | They propose to fit a representation function to predict an oracle embedding vector based on limited contexts. |
| Outcome: | The proposed model outperforms existing methods in constructing an accurate embedding for OOV words and improves downstream tasks when the embeddable is utilized. |