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Found 5 papers, 1 papers with code
Aalap: AI Assistant for Legal & Paralegal Functions in India
Using proprietary Large Language Models on legal tasks poses challenges due to data privacy issues, domain data heterogeneity, domain knowledge sophistication, and domain objectives uniqueness.
SemEval 2023 Task 6: LegalEval - Understanding Legal Texts
LegalEval task has three sub-tasks: Task-A (Rhetorical Roles Labeling) is about automatically structuring legal documents into semantically coherent units, Task-B (Legal Named Entity Recognition) deals with identifying relevant entities in a legal document and Task-C (Court Judgement Prediction with Explanation) explores the possibility of automatically predicting the outcome of a legal case along with providing an explanation for the prediction.
Named Entity Recognition in Indian court judgments
Identification of named entities from legal texts is an essential building block for developing other legal Artificial Intelligence applications.
Corpus for Automatic Structuring of Legal Documents
In this paper, we introduce a new corpus for structuring legal documents.
Indian Legal NLP Benchmarks : A Survey
Availability of challenging benchmarks is the key to advancement of AI in a specific field. Since Legal Text is significantly different than normal English text, there is a need to create separate Natural Language Processing benchmarks for Indian Legal Text which are challenging and focus on tasks specific to Legal Systems.
