Plus Strategies are Exponentially Slower for Planted Optima of Random Height. - Johannes Lengler; Leon Schiller; Oliver Sieberling (GECCO, 2024)

EvoPress: Towards Optimal Dynamic Model Compression via Evolutionary Search. - Oliver Sieberling; Denis Kuznedelev; Eldar Kurtic; Dan Alistarh (CoRR, 2024)

DarwinLM: Evolutionary Structured Pruning of Large Language Models. - Shengkun Tang; Oliver Sieberling; Eldar Kurtic; Zhiqiang Shen; Dan Alistarh (CoRR, 2025)

Quartet: Native FP4 Training Can Be Optimal for Large Language Models. - Roberto L. Castro; Andrei Panferov; Soroush Tabesh; Oliver Sieberling; Jiale Chen 004; Mahdi Nikdan; Saleh Ashkboos; Dan Alistarh (CoRR, 2025)

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training. - Johannes von Oswald; Nino Scherrer; Seijin Kobayashi; Luca Versari; Songlin Yang; Maximilian Schlegel; Kaitlin Maile; Yanick Schimpf; Oliver Sieberling; Alexander Meulemans; Rif A. Saurous; Guillaume Lajoie; et al. (CoRR, 2025)

Hardest Monotone Functions for Evolutionary Algorithms. - Marc Kaufmann; Maxime Larcher; Johannes Lengler; Oliver Sieberling (SN Comput. Sci., 2025)