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New LLM approach enhances legal judgment summarization using Tree of Thoughts

Researchers have developed a new hybrid approach for summarizing legal case judgments using Large Language Models (LLMs). This method combines extractive and abstractive summarization techniques, inspired by the Tree of Thoughts framework. Experiments conducted with DeepSeek and LLama models indicate that this novel extractive-abstractive prompt yields superior summaries compared to traditional extractive or abstractive methods alone. AI

IMPACT This research could improve the efficiency and accuracy of legal document analysis for legal professionals.

RANK_REASON The cluster contains an academic paper detailing a new methodology for LLM summarization.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New LLM approach enhances legal judgment summarization using Tree of Thoughts

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Aniket Deroy, Kripabandhu Ghosh, Saptarshi Ghosh ·

    A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

    arXiv:2606.28044v1 Announce Type: new Abstract: In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditional extractive and abstractive summarization of case judgements. However, hybrid o…

  2. arXiv cs.CL TIER_1 English(EN) · Saptarshi Ghosh ·

    A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

    In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditional extractive and abstractive summarization of case judgements. However, hybrid or extractive-abstractive techniques have not bee…