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Reliable, Reproducible, and Really Fast Leaderboards with Evalica

2024/12/15 by Dmitry Ustalov, Ustalov, Dmitry · 2 citations
Computer Science · #Music Technology and Sound Studies #Artificial Intelligence in Games

paper · pdf · doi:10.48550/arxiv.2412.11314

Abstract

The rapid advancement of natural language processing (NLP) technologies, such as instruction-tuned large language models (LLMs), urges the development of modern evaluation protocols with human and machine feedback. We introduce Evalica, an open-source toolkit that facilitates the creation of reliable and reproducible model leaderboards. This paper presents its design, evaluates its performance, and demonstrates its usability through its Web interface, command-line interface, and Python API.

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