Evaluation Artefacts for LLM@PR: A LLM-driven Petition Ranking Framework
收藏Zenodo2025-05-23 更新2026-05-26 收录
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https://zenodo.org/doi/10.5281/zenodo.15496401
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资源简介：
This repository contains evaluation artefacts supporting the paper:"LLMPR: A Novel LLM-Driven Transfer Learning based Petition Ranking Model" (submitted to Artificial Intelligence and Law, 2025).
The files include:- Test-set predictions for all models used (LightGBM regressors with embeddings and numeric features)- Bootstrapped 95% confidence intervals for Tolerance-10% accuracy- Duplicate-content validation metrics- A metrics summary table across models
All results are based on the ILDC dataset with its official train/test split. The code used for this evaluation is compatible with Python 3.8+ and scikit-learn, LightGBM, numpy, pandas.
See `README_LLMPR_Artefacts.md` for details and reproduction instructions.
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Zenodo创建时间：
2025-05-23
