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cs.AI2026
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…
cs.IR2026
Ensembles at Any Cost? Accuracy-Energy Trade-offs in Recommender Systems
Jannik Nitschke, Lukas Wegmeth, Joeran Beel
Ensemble methods are frequently used in recommender systems to improve accuracy by combining multiple models. Recent work reports sizable performance gains, but most studies still…