Papers by Simon Coumes
TINA: Textual Inference with Negation Augmentation (2022.findings-emnlp)
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| Challenge: | Existing transformer-based models perform poorly on textual entailment when examples contain negations. |
| Approach: | They propose a new definition of textual entailment that captures negation and a principled technique for negated data augmentation that can be combined with unlikelihood loss function. |
| Outcome: | The proposed method significantly improves on textual entailment datasets with negations without sacrificing performance on datasets without negation. |