Matthias Aßenmacher

According to our database, Matthias Aßenmacher authored at least 19 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Divergent Token Metrics: Measuring degradation to prune away LLM components - and optimize quantization.

Björn Deiseroth, Max Meuer, Nikolas Gritsch, Constantin Eichenberg, Patrick Schramowski, Matthias Aßenmacher, Kristian Kersting

CoRR, 2023

How Prevalent is Gender Bias in ChatGPT? - Exploring German and English ChatGPT Responses.

Stefanie Urchs, Veronika Thurner, Matthias Aßenmacher, Christian Heumann, Stephanie Thiemichen

CoRR, 2023

Classifying multilingual party manifestos: Domain transfer across country, time, and genre.

Matthias Aßenmacher, Nadja Sauter, Christian Heumann

CoRR, 2023

How Different Is Stereotypical Bias Across Languages?

Ibrahim Tolga Öztürk, Rostislav Nedelchev, Christian Heumann, Esteban Garces Arias, Marius Roger, Bernd Bischl, Matthias Aßenmacher

CoRR, 2023

Multimodal Deep Learning.

Cem Akkus, Luyang Chu, Vladana Djakovic, Steffen Jauch-Walser, Philipp Koch, Giacomo Loss, Christopher Marquardt, Marco Moldovan, Nadja Sauter, Maximilian Schneider, Rickmer Schulte, Karol Urbanczyk, Jann Goschenhofer, Christian Heumann, Rasmus Hvingelby, Daniel Schalk, Matthias Aßenmacher

CoRR, 2023

A tailored Handwritten-Text-Recognition System for Medieval Latin.

Philipp Koch, Gilary Vera Nuñez, Esteban Garces Arias, Christian Heumann, Matthias Schöffel, Alexander Häberlin, Matthias Aßenmacher

Proceedings of the Ancient Language Processing Workshop, 2023

ActiveGLAE: A Benchmark for Deep Active Learning with Transformers.

Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering.

Matthias Aßenmacher, Lukas Rauch, Jann Goschenhofer, Andreas Stephan, Bernd Bischl, Benjamin Roth, Bernhard Sick

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), 2023

Automatic Transcription of Handwritten Old Occitan Language.

Esteban Garces Arias, Vallari Pai, Matthias Schöffel, Christian Heumann, Matthias Aßenmacher

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

On the Current State of Reproducibility and Reporting of Uncertainty for Aspect-Based Sentiment Analysis.

Elisabeth Lebmeier, Matthias Aßenmacher, Christian Heumann

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Pre-trained language models evaluating themselves - A comparative study.

Philipp Koch, Matthias Aßenmacher, Christian Heumann

Proceedings of the Third Workshop on Insights from Negative Results in NLP, 2022

2021

Comparability, evaluation and benchmarking of large pre-trained language models.

Matthias Aßenmacher

PhD thesis, 2021

Benchmarking down-scaled (not so large) pre-trained language models.

Matthias Aßenmacher, Patrick Schulze, Christian Heumann

CoRR, 2021

Exploring Topic-Metadata Relationships with the STM: A Bayesian Approach.

Patrick Schulze, Simon Wiegrebe, Paul W. Thurner, Christian Heumann, Matthias Aßenmacher, Sandra Wankmüller

CoRR, 2021

Re-Evaluating GermEval17 Using German Pre-Trained Language Models.

Matthias Aßenmacher, Alessandra Corvonato, Christian Heumann

Proceedings of the Swiss Text Analytics Conference 2021, Winterthur, 2021

A New Benchmark for NLP in Social Sciences: Evaluating the Usefulness of Pre-trained Language Models for Classifying Open-ended Survey Responses.

Maximilian Meidinger, Matthias Aßenmacher

Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

2020

Pre-trained language models as knowledge bases for Automotive Complaint Analysis.

V. D. Viellieber, Matthias Aßenmacher

CoRR, 2020

On the Comparability of Pre-trained Language Models.

Matthias Aßenmacher, Christian Heumann

Proceedings of the 5th Swiss Text Analytics Conference and the 16th Conference on Natural Language Processing, 2020

Evaluating Unsupervised Representation Learning for Detecting Stances of Fake News.

Maike Guderlei, Matthias Aßenmacher

Proceedings of the 28th International Conference on Computational Linguistics, 2020