Papers by Joshua Bensemann
AbductionRules: Training Transformers to Explain Unexpected Inputs (2022.findings-acl)
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| Challenge: | AbductionRules is a set of natural language datasets designed to train and test generalisable abduction over natural-language knowledge bases. |
| Approach: | They propose to train and test generalisable abduction over natural-language knowledge bases by using natural language datasets to fine tune pre-trained Transformers. |
| Outcome: | The proposed models learned generalisable abduction techniques but also exploited the structure of the datasets. |