Investigating Transformer-Guided Chaining for Interpretable Natural Logic Reasoning (2023.findings-acl)
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| Challenge: | Natural logic reasoning has received increasing attention lately, with several datasets and neural models proposed, though with limited success. |
| Approach: | They propose to iteratively perform 1-step neural inferences and chain together the results to generate a multi-step reasoning trace. |
| Outcome: | The proposed method has high accuracies on a multi-hop First-Order Logic (FOL) reasoning benchmark. |
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