English

Jury: A Comprehensive Evaluation Toolkit

Computation and Language 2024-05-21 v2 Artificial Intelligence

Abstract

Evaluation plays a critical role in deep learning as a fundamental block of any prediction-based system. However, the vast number of Natural Language Processing (NLP) tasks and the development of various metrics have led to challenges in evaluating different systems with different metrics. To address these challenges, we introduce jury, a toolkit that provides a unified evaluation framework with standardized structures for performing evaluation across different tasks and metrics. The objective of jury is to standardize and improve metric evaluation for all systems and aid the community in overcoming the challenges in evaluation. Since its open-source release, jury has reached a wide audience and is available at https://github.com/obss/jury.

Keywords

Cite

@article{arxiv.2310.02040,
  title  = {Jury: A Comprehensive Evaluation Toolkit},
  author = {Devrim Cavusoglu and Secil Sen and Ulas Sert and Sinan Altinuc},
  journal= {arXiv preprint arXiv:2310.02040},
  year   = {2024}
}

Comments

authors order corrected

R2 v1 2026-06-28T12:39:24.992Z