activity
20212026
most citedNL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

25 citations · 30 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2026★ 1 cited

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

Soofi-Team, :, Benedikt Droste +30

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.CL2025

New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models

Julia Wunderle, Anton Ehrmanntraut, Jan Pfister +2

Encoders remain essential for efficient German NLP and NLU scenarios despite the rise of decoder-only LLMs. This work studies two routes to high-quality German encoders under ident…

cs.CL2024

LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Jan Pfister, Julia Wunderle, Andreas Hotho

We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…

cs.IR2024★ 4 cited

BibSonomy Meets ChatLLMs for Publication Management: From Chat to Publication Management: Organizing your related work using BibSonomy & LLMs

Tom Völker, Jan Pfister, Tobias Koopmann +1

The ever-growing corpus of scientific literature presents significant challenges for researchers with respect to discovery, management, and annotation of relevant publications. Tra…

cs.LG2023

Higher-Order DeepTrails: Unified Approach to *Trails

Tobias Koopmann, Jan Pfister, André Markus +3

Analyzing, understanding, and describing human behavior is advantageous in different settings, such as web browsing or traffic navigation. Understanding human behavior naturally he…

cs.CL2021★ 25 cited

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122

Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…