LogiGraph: Logical Reasoning with Contrastive Learning and Lightweight Graph Networks (2025.coling-main)
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| Challenge: | Existing methods emphasize contextual semantics while others pay more attention to explicit logical features. Existing models utilize graph convolutional networks (GCN) for node updates, still exhibiting some shortcomings. |
| Approach: | They propose a logical reasoning method with contrastive learning and lightweight graph networks (LogiGraph) they employ conjunction and punctuation marks as two types of edges to construct a dual graph. |
| Outcome: | The proposed method improves the GCN and employs conjunction and punctuation marks as two types of edges to construct a dual graph. |
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