collaborators

6 papers

cs.CL2026

A Sovereign, Open-Source Foundation Model for German and English

The Soofi-Team, Soofi-Team, : +31

We present Soofi S 30B-A3B, a sovereign, open-source Mixture-of-Experts (MoE) hybrid Mamba Transformer foundation model for German and English. Its hybrid design activates only 3B…

cs.CL2026

KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full Report

Maurice Kraus, Ruben Härle, Sebastian Sztwiertnia +5

High-quality pretraining data is a central ingredient in modern language models, but German-language resources remain far less developed than their English counterparts: they are o…

cs.LG2026

Modalities, a PyTorch-native Framework For Large-scale LLM Training and Research

Max Lübbering, Timm Ruland, Richard Rutmann +8

Today's LLM (pre-) training and research workflows typically allocate a significant amount of compute to large-scale ablation studies. Despite the substantial compute costs of thes…

cs.CL2025

Teuken-7B-Base & Teuken-7B-Instruct: Towards European LLMs

Mehdi Ali, Michael Fromm, Klaudia Thellmann +38

We present two multilingual LLMs, Teuken 7B-base and Teuken 7B-instruct, designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European U…

cs.CL2025

Data Processing for the OpenGPT-X Model Family

Nicolo' Brandizzi, Hammam Abdelwahab, Anirban Bhowmick +19

This paper presents a comprehensive overview of the data preparation pipeline developed for the OpenGPT-X project, a large-scale initiative aimed at creating open and high-performa…

cs.CL2025

Judging Quality Across Languages: A Multilingual Approach to Pretraining Data Filtering with Language Models

Mehdi Ali, Manuel Brack, Max Lübbering +15

High-quality multilingual training data is essential for effectively pretraining large language models (LLMs). Yet, the availability of suitable open-source multilingual datasets r…