重新构想法律判决：PredEx 与印度法院智能 AI 解释的兴起
Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts
AI总结：
本文提出印度法律领域最大的专家标注数据集 PredEx，通过指令微调大语言模型提升法律判决预测的准确性与可解释性，为法律界和 NLP 社区建立了有价值的基准。
摘要：
在大语言模型（LLMs）时代，由于法律程序的复杂性和专家标注数据集的稀缺，预测司法结果面临重大挑战。针对这一问题，我们提出了 PredEx（Prediction with Explanation），这是印度语境下最大的法律判决预测与解释专家标注数据集，包含超过 15,000 条标注。这一开创性的语料库显著增强了 AI 模型在法律分析中的训练与评估，其创新之处包括将指令微调应用于大语言模型。该方法显著提高了这些模型在法律判决方面的预测准确性和解释深度。我们采用了多种基于 Transformer 的模型，分别针对通用语境和印度法律语境进行了适配。通过严格的词汇、语义和专家评估，我们的模型有效利用 PredEx 提供精确的预测和有意义的解释，使其成为法律界和 NLP 社区一个有价值的基准。
英文摘要：
In the era of Large Language Models (LLMs), predicting judicial outcomes poses significant challenges due to the complexity of legal proceedings and the scarcity of expert-annotated datasets. Addressing this, we introduce \textbf{Pred}iction with \textbf{Ex}planation (\texttt{PredEx}), the largest expert-annotated dataset for legal judgment prediction and explanation in the Indian context, featuring over 15,000 annotations. This groundbreaking corpus significantly enhances the training and evaluation of AI models in legal analysis, with innovations including the application of instruction tuning to LLMs. This method has markedly improved the predictive accuracy and explanatory depth of these models for legal judgments. We employed various transformer-based models, tailored for both general and Indian legal contexts. Through rigorous lexical, semantic, and expert assessments, our models effectively leverage \texttt{PredEx} to provide precise predictions and meaningful explanations, establishing it as a valuable benchmark for both the legal profession and the NLP community.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
