Papers by Mike Izbicki
DocSplit: Simple Contrastive Pretraining for Large Document Embeddings (2023.findings-emnlp)
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| Challenge: | Existing model pretraining methods only consider local information, resulting in low-quality embeddings for large documents. |
| Approach: | They propose a new method which forces models to consider the entire global context of a large document. |
| Outcome: | The proposed method outperforms existing models on document classification, few shot learning, and retrieval tasks. |