Estimating the Pruned Search Space Size of Subgroup Discovery. - Lennart Purucker; Felix I. Stamm; Florian Lemmerich; Joeran Beel (ICDM, 2022)

CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure. - Lennart Oswald Purucker; Joeran Beel (AutoML, 2023)

Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML. - Lennart Oswald Purucker; Lennart Schneider; Marie Anastacio; Joeran Beel; Bernd Bischl; Holger H. Hoos (AutoML, 2023)

The Effect of Random Seeds for Data Splitting on Recommendation Accuracy. - Lukas Wegmeth; Tobias Vente; Lennart Purucker; Joeran Beel (Perspectives@RecSys, 2023)

Assembled-OpenML: Creating Efficient Benchmarks for Ensembles in AutoML with OpenML. - Lennart Purucker; Joeran Beel (CoRR, 2023)

Don't Waste Your Time: Early Stopping Cross-Validation. - Edward Bergman; Lennart Purucker; Frank Hutter (AutoML, 2024)

DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation. - Alexander Pfefferle; Lennart Purucker; Frank Hutter (MedSAM@CVPR, 2024)

Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems. - Lukas Wegmeth; Tobias Vente; Lennart Purucker (ECIR (1), 2024)

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models. - Rhea Sukthanker; Arber Zela; Benedikt Staffler; Aaron Klein; Lennart Purucker; Jörg K. H. Franke; Frank Hutter (NeurIPS, 2024)

Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost. - Jannis Maier; Felix Möller; Lennart Purucker (CoRR, 2024)

Dynamic Post-Hoc Neural Ensemblers. - Sebastian Pineda-Arango; Maciej Janowski; Lennart Purucker; Arber Zela; Frank Hutter; Josif Grabocka (CoRR, 2024)

Large Language Models Engineer Too Many Simple Features For Tabular Data. - Jaris Küken; Lennart Purucker; Frank Hutter (CoRR, 2024)

Ensembling Finetuned Language Models for Text Classification. - Sebastian Pineda-Arango; Maciej Janowski; Lennart Purucker; Arber Zela; Frank Hutter; Josif Grabocka (CoRR, 2024)

Transfer Learning for Finetuning Large Language Models. - Tobias Strangmann; Lennart Purucker; Jörg K. H. Franke; Ivo Rapant; Fabio Ferreira; Frank Hutter (CoRR, 2024)

Efficient MedSAMs: Segment Anything in Medical Images on Laptop. - Jun Ma 016; Feifei Li 010; Sumin Kim; Reza Asakereh; Bao-Hiep Le; Dang-Khoa Nguyen-Vu; Alexander Pfefferle; Muxin Wei; Ruochen Gao; Donghang Lyu; Songxiao Yang; Lennart Purucker; et al. (CoRR, 2024)

AMLTK: A Modular AutoML Toolkit in Python. - Edward Bergman; Matthias Feurer; Aron Bahram; Amir Rezaei Balef; Lennart Purucker; Sarah Segel; Marius Lindauer; Frank Hutter; Katharina Eggensperger (J. Open Source Softw., 2024)

TabPFN. - Noah Hollmann; Frank Hutter; Samuel Gabriel Müller; Lennart Purucker; Arjun Krishnakumar; Max Körfer; Robin Tibor Schirrmeister (Zenodo, 2024)

OpenML: Insights from 10 years and more than a thousand papers. - Bernd Bischl; Giuseppe Casalicchio; Taniya Das; Matthias Feurer; Sebastian Fischer; Pieter Gijsbers; Subhaditya Mukherjee; Andreas C. Müller 002; László Németh; Luis Oala; Lennart Purucker; Sahithya Ravi; et al. (Patterns, 2025)

Accurate predictions on small data with a tabular foundation model. - Noah Hollmann; Samuel Müller 005; Lennart Purucker; Arjun Krishnakumar; Max Körfer; Shi Bin Hoo; Robin Tibor Schirrmeister; Frank Hutter (Nat., 2025)

Unreflected Use of Tabular Data Repositories Can Undermine Research Quality. - Andrej Tschalzev; Lennart Purucker; Stefan Lüdtke; Frank Hutter; Christian Bartelt; Heiner Stuckenschmidt (CoRR, 2025)

TabArena: A Living Benchmark for Machine Learning on Tabular Data. - Nick Erickson; Lennart Purucker; Andrej Tschalzev; David Holzmüller; Prateek Mutalik Desai; David Salinas; Frank Hutter (CoRR, 2025)

Early Stopping Tabular In-Context Learning. - Jaris Küken; Lennart Purucker; Frank Hutter (CoRR, 2025)

MARVIS: Modality Adaptive Reasoning over VISualizations. - Benjamin Feuer; Lennart Purucker; Oussama Elachqar; Chinmay Hegde (CoRR, 2025)

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data. - Anurag Garg; Muhammad Ali; Noah Hollmann; Lennart Purucker; Samuel Müller 005; Frank Hutter (CoRR, 2025)

Towards Benchmarking Foundation Models for Tabular Data With Text. - Martin Mráz; Breenda Das; Anshul Gupta; Lennart Purucker; Frank Hutter (CoRR, 2025)

How Usable is Automated Feature Engineering for Tabular Data? - Bastian Schäfer; Lennart Purucker; Maciej Janowski; Frank Hutter (CoRR, 2025)