Papers by Audi Primadhanty
Entity Disambiguation on a Tight Labeling Budget (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing approaches to training entity disambiguation models require a small labeling budget . a defense research analyst might need to map military equipment to a knowledge base describing emergent defense technologies. |
| Approach: | They propose a method that combines feature diversity with low rank correction . they use bilinear tensor models to train a model that uses a rich representation of context . |
| Outcome: | The proposed approach reduces the amount of labeled data necessary to achieve a given performance. |
Analyzing Text Representations by Measuring Task Alignment (2023.acl-short)
Copied to clipboard
| Challenge: | Recent advances in text classification have shown that pre-trained representations are key for text classification. |
| Approach: | They propose a task alignment score that measures alignment at different levels of granularity. |
| Outcome: | The proposed score shows that task alignment can explain the performance of a given representation. |