Papers with expressive representations of legal arguments

1 papers
Fine-Grained Legal Argument-Pair Extraction via Coarse-Grained Pre-training (2024.lrec-main)

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Challenge: Current methods conceptualize LAE as a supervised sentence-pair classification problem and necessitate extensive manual annotations.
Approach: They propose a model that focuses on fine-grained alignment of argument pairs building upon coarse-grain complaint-defense pairs.
Outcome: The proposed model outperforms baseline models by 3.7 and 2.4 points on average.

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