{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/dale-generative-data-augmentation-for-low","title":"DALE: Generative Data Augmentation for Low-Resource Legal NLP","arxiv_id":"2310.15799","date":"2023-10-24","proceeding":null,"authors":["Sreyan Ghosh","Chandra Kiran Evuru","Sonal Kumar","S Ramaneswaran","S Sakshi","Utkarsh Tyagi","Dinesh Manocha"],"abstract":"We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. 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