Semantic Precedent Retriever for Rapid Litigation Strategy Drafting
Keywords:
semantic retrieval, precedent indexing, dense vector models, litigation strategy, legal informatics, probability-of-successAbstract
The objective of this paper is to present a framework which introduces rich semantic retrieval models for indexing large case law and regulatory opinions to speed litigation strategy creation. Advanced vector-based retrieval methods may find legally relevant precedents that match sophisticated user queries. A generative portion then assembles argument skeletons with key citations, counter-argument considerations, and success metrics based on historical data.
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