Augmenting Legal Judgment Prediction with Contrastive Case Relations (2022.coling-1)
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| Challenge: | Existing legal judgment prediction methods only consider one case fact description as input, which may not fully utilize information in the data such as case relations and frequency. |
| Approach: | They propose a new perspective that introduces some contrastive case relations to construct case triples as input and a corresponding judgment prediction framework with case triple modeling. |
| Outcome: | The proposed framework can be used to refine encoding and decoding processes using three customized modules on two public datasets. |
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