AutoRecLab

AutoRecLab: An Autonomous Recommender Systems Lab

Abstract. Recommender systems (RecSys) research depends on extensive empirical evaluation, yet translating experimental designs into executable code remains a manual, error-prone process. This paper presents AutoRecLab, a Python-based autonomous RecSys lab that automates RecSys experimentation from natural-language prompts. Starting from a research idea, AutoRecLab derives explicit experiment requirements, develops and Read more…

By Joeran Beel, ago

From AutoRecSys to AutoRecLab: A Call to Build, Evaluate, and Govern Autonomous Recommender-Systems Research Labs

Joeran Beel (University of Siegen, Germany) Bela Gipp (University of Göttingen, Germany) Tobias Vente (University of Antwerp, Belgium) Moritz Baumgart (University of Siegen, Germany) Philipp Meister (University of Göttingen, Germany) Pre-Print @misc{beel2025autorecsysautoreclabbuildevaluate, title={From AutoRecSys to AutoRecLab: A Call to Build, Evaluate, and Govern Autonomous Recommender-Systems Research Labs}, author={Joeran Beel and Read more…

By Joeran Beel, ago