Papers by Mahdi Rahimi
Do Transformer Networks Improve the Discovery of Rules from Text? (2022.lrec-1)
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| Challenge: | Existing rules that model binary relations such as X treat Y are based on the distributional hypothesis of Harris (1954). |
| Approach: | They propose to implement the distributional hypothesis using contextualized embeddings provided by a transformer-network-based language model to measure the similarity between slots instead of lexical overlap. |
| Outcome: | The proposed approach outperforms the original DIRT algorithm in the question answering-based evaluation. |