RecList is an open source library providing behavioral, “black-box” testing for recommender systems. Inspired by the pioneering work of Ribeiro et al. 2020 in NLP, we introduce a general plug-and-play procedure to scale up behavioral testing, with an easy-to-extend interface for custom use cases.
To streamline comparisons among existing models, RecList ships with popular datasets and ready-made behavioral tests: read the our TDS blog post as a gentle introduction to the main use cases, and try out our colab to get started with the code.
We are actively working towards our beta, with new capabilities and improved documentation and tutorials: check back often here and on Github for updates!
Star our GitHub project!
Our 2022 Web Conf Paper.
Our Video at Stitch Fix Algo Hour.
Coveo's Director of A.I, combining product thinking and research-like curiosity to build better data-driven systems at scale.
Federico is a PostDoctoral Researcher at Stanford University. Working on Natural Language Processing.