ReLeVAnT achieves 99.3% accuracy and 98.7% F1 in binary legal document classification on LexGLUE via n-gram processing, contrastive score matching, and a shallow neural network after one-time keyword extraction.
In Findings of the Association for Computational Lin- guistics: NAACL 2022, pages 2208–2221
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ReLeVAnT: Relevance Lexical Vectors for Accurate Legal Text Classification
ReLeVAnT achieves 99.3% accuracy and 98.7% F1 in binary legal document classification on LexGLUE via n-gram processing, contrastive score matching, and a shallow neural network after one-time keyword extraction.