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Computer Science > Computation and Language

arXiv:2410.10030 (cs)
[Submitted on 13 Oct 2024]

Title:A Step Towards Mixture of Grader: Statistical Analysis of Existing Automatic Evaluation Metrics

Authors:Yun Joon Soh, Jishen Zhao
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Abstract:The explosion of open-sourced models and Question-Answering (QA) datasets emphasizes the importance of automated QA evaluation. We studied the statistics of the existing evaluation metrics for a better understanding of their limitations. By measuring the correlation coefficients of each evaluation metric concerning human-like evaluation score, we observed the following: (1) existing metrics have a high correlation among them concerning the question type (e.g., single word, single phrase, etc.), (2) no single metric can adequately estimate the human-like evaluation. As a potential solution, we discuss how a Mixture Of Grader could potentially improve the auto QA evaluator quality.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2410.10030 [cs.CL]
  (or arXiv:2410.10030v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2410.10030

Submission history

From: Yun Joon Soh [view email]
[v1] Sun, 13 Oct 2024 22:10:42 UTC (348 KB)
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