Papers by Ron Di Carlantonio
Neural Document Segmentation Using Weighted Sliding Windows with Transformer Encoders (2025.coling-industry)
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| Challenge: | Using overlapping text sequences and position-aware weighting, we achieve up to a 10% increase in segmentation F1 score compared to existing methods. |
| Approach: | They propose a Transformer-based method for document segmentation that utilizes overlapping text sequences with a unique position-aware weighting mechanism to enhance segmentation accuracy. |
| Outcome: | The proposed method achieves up to 10% increase in segmentation F1 score compared to existing methods and improves quality of generated responses by 5% while achieving four times greater efficiency. |