Legal text summarization with optimized hybrid models and fine-tuned LLaMA-2
Abstract Legal document summarization presents a critical challenge due to the dense, complex nature and extreme length of legal texts. This paper proposes and evaluates two distinct methods for this task. The first is an optimized hybrid model that combines TextRank for extractive summarization wit...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Springer
2026-01-01
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| Schriftenreihe: | Discover Computing |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1007/s10791-026-09916-y |
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