Praetor: A Fine-Grained Generative LLM Evaluator with Instance-Level Customizable Evaluation Criteria

Yongqi Leng, Renren Jin, Yue Chen, Zhuowen Han, Ling Shi, Jianxiang Peng, Lei Yang, Juesi Xiao, Deyi Xiong. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.acl-long.513
Citations
1
Primary Topic
Digital Rights Management and Security
Type
article
Field-Weighted Citation Impact
3.25

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article

Praetor: A Fine-Grained Generative LLM Evaluator with Instance-Level Customizable Evaluation Criteria

Zhuowen Han, Renren Jin, Yongqi Leng, Ling Shi et al.
1 citations
Digital Rights Management and Security
3.25
article

Praetor: A Fine-Grained Generative LLM Evaluator with Instance-Level Customizable Evaluation Criteria

Zhuowen Han, Renren Jin, Yongqi Leng, Ling Shi, Jianxiang Peng, Yue Chen, Juesi Xiao, Deyi Xiong, Yang Lei
article en
1 citations

Abstract

Yongqi Leng, Renren Jin, Yue Chen, Zhuowen Han, Ling Shi, Jianxiang Peng, Lei Yang, Juesi Xiao, Deyi Xiong. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

National Key Research and Development Program of China
Openalex Percentile: Top 7%
Digital Rights Management and Security
3.25
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Praetor: A Fine-Grained Generative LLM Evaluator with Instance-Level Customizable Evaluation Criteria — Zhuowen Han, Renren Jin, et al. · (2025) | TGRS Research Map | TGRS