1 citations · 1 across the 3 of their papers we have counts for
4 papers
AutoRecLab: Describe the Experiment, Get the Code!
Moritz Baumgart, Philipp Meister, Justus Krell +3
Empirical evaluation is central to recommender-systems (RecSys) research, but turning experimental designs into executable code remains a manual and error-prone task. We present Au…
From AutoRecSys to AutoRecLab: A Call to Build, Evaluate, and Govern Autonomous Recommender-Systems Research Labs
Joeran Beel, Bela Gipp, Tobias Vente +2
Recommender-systems research has accelerated model and evaluation advances, yet largely neglects automating the research process itself. We argue for a shift from narrow AutoRecSys…
Evaluating Sakana's AI Scientist: Bold Claims, Mixed Results, and a Promising Future?
Joeran Beel, Min-Yen Kan, Moritz Baumgart
A major step toward Artificial General Intelligence (AGI) and Super Intelligence is AI's ability to autonomously conduct research - what we term Artificial Research Intelligence (A…
e-Fold Cross-Validation for Recommender-System Evaluation
Moritz Baumgart, Lukas Wegmeth, Tobias Vente +1
To combat the rising energy consumption of recommender systems we implement a novel alternative for k-fold cross validation. This alternative, named e-fold cross validation, aims t…