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cs.LG2026
CEDAR: Context Engineering for Agentic Data Science
Rishiraj Saha Roy, Chris Hinze, Luzian Hahn +1
We demonstrate CEDAR, an application for automating data science (DS) tasks with an agentic setup. Solving DS problems with LLMs is an underexplored area that has immense market va…
cs.LG2025
Pre-Training LLMs on a budget: A comparison of three optimizers
Joel Schlotthauer, Christian Kroos, Chris Hinze +3
Optimizers play a decisive role in reducing pre-training times for LLMs and achieving better-performing models. In this study, we compare three major variants: the de-facto standar…