Reliable, Reproducible, and Really Fast Leaderboards with Evalica
Authors: name: Dmitry Ustalov

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.