Research Group Valentin Hofmann
Valentin Hofmann
Prof. Dr.
Collaborating PI
Valentin Hofmann
a Junior Professor for Information and Language Processing Using AI Methods at LMU Munich.
His work integrates machine learning with insights from linguistics and social science to identify and address limitations in natural language processing systems. Currently, he focus on large language models, particularly in the areas of tokenization, sociolinguistic grounding, and bias.
Recent News @MCML
Publications @MCML
2026
[7]
F. Lin • V. Hofmann • X. Wan • W. Wang • Z. Ding • A. G. Cohn • J. B. Pierrehumbert
Can Large Language Models Generalize Procedures Across Representations?
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
Can Large Language Models Generalize Procedures Across Representations?
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
2024
[6]
V. Hofmann • L. Weissweiler • D. Mortensen • H. Schütze • J. Pierrehumbert
Derivational Morphology Reveals Analogical Generalization in Large Language Models.
Preprint (Nov. 2024). arXiv
Derivational Morphology Reveals Analogical Generalization in Large Language Models.
Preprint (Nov. 2024). arXiv
2023
[5]
L. Weissweiler • V. Hofmann • A. Kantharuban • A. Cai • R. Dutt • A. Hengle • A. Kabra • A. Kulkarni • A. Vijayakumar • H. Yu • H. Schütze • K. Oflazer • D. Mortensen
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model.
EMNLP 2023 - Conference on Empirical Methods in Natural Language Processing. Singapore, Dec 06-10, 2023. DOI
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model.
EMNLP 2023 - Conference on Empirical Methods in Natural Language Processing. Singapore, Dec 06-10, 2023. DOI
[4]
V. Hofmann
Computational investigations of derivational morphology.
Dissertation University of Oxford. Oct. 2023. Co-Supervised. DOI
Computational investigations of derivational morphology.
Dissertation University of Oxford. Oct. 2023. Co-Supervised. DOI
[3]
L. Weissweiler • V. Hofmann • A. Köksal • H. Schütze
Explaining pretrained language models' understanding of linguistic structures using construction grammar.
Frontiers in Artificial Intelligence 6. Oct. 2023. DOI
Explaining pretrained language models' understanding of linguistic structures using construction grammar.
Frontiers in Artificial Intelligence 6. Oct. 2023. DOI
2022
[2]
L. Weissweiler • V. Hofmann • A. Köksal • H. Schütze
The better your Syntax, the better your Semantics? Probing Pretrained Language Models for the English Comparative Correlative.
EMNLP 2022 - Conference on Empirical Methods in Natural Language Processing. Abu Dhabi, United Arab Emirates, Nov 07-11, 2022. DOI
The better your Syntax, the better your Semantics? Probing Pretrained Language Models for the English Comparative Correlative.
EMNLP 2022 - Conference on Empirical Methods in Natural Language Processing. Abu Dhabi, United Arab Emirates, Nov 07-11, 2022. DOI
[1]
L. Weissweiler • V. Hofmann • M. J. Sabet • H. Schütze
CaMEL: Case Marker Extraction without Labels.
ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics. Dublin, Ireland, May 22-27, 2022. DOI
CaMEL: Case Marker Extraction without Labels.
ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics. Dublin, Ireland, May 22-27, 2022. DOI
©all images: LMU | TUM
Back to Top
2026-04-01 - Last modified: 2026-07-03