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Chair of Computational Linguistics

Prof. Dr. Annemarie Friedrich

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Computational Linguistics?is an interdisciplinary field that combines the study of linguistics and computer science to investigate the computational aspects of human language. It focuses on developing and applying computational models and algorithms to analyze, understand, and generate natural language.

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Digital Humanities?(DH)?is an interdisciplinary field that combines traditional humanities disciplines, such as literature, history, philosophy, linguistics, and art, with digital technologies and computational methods. It aims to study, interpret, and analyze cultural and historical artifacts using digital tools and methodologies.

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? 新万博体育下载_万博体育app【投注官网】 of Augsburg

The core research interests of my group are within computational linguistics and natural language processing with a focus on semantics and information extraction from text, i.e, natural language understanding ("Sprachverstehen"). I am particularly interested in annotation and corpus creation, as any machine-learning model depends on the underlying data.

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In the?machine-learning?oriented part of my research,?I work on text mining for scientific text, syntactic and semantic parsing, and uncertainty in the context of deep learning for NLP. The?corpus-linguistic?part of my research has focused on?understanding and modeling interactions at the syntax-semantics interface, taking into account influences of discourse and pragmatics. Most of my past research is about the computational modeling of aspect, genericity, and modal verbs.

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I am currently the vice president of the?German Society for Computational Linguistics?(GSCL), the scientific association in the German-speaking countries and regions for research, teaching and professional work in natural language processing. I am a member of the ACL Special Interest Group for Annotation (ACL SIGANN).

Group Members

Prof. Dr. Annemarie Friedrich
Professor
Lehrstuhl für Computerlinguistik
  • Phone: +49 821 598 4628
  • Email:
  • Room 1022 (Building BCM)
Sabrina Achberger
Team Assistant
Lehrstuhl für Computerlinguistik
  • Room 1023 (Building BCM)
Fabio Mariani
Wissenschaftlicher Mitarbeiter / Researcher
Lehrstuhl für Computerlinguistik
  • Room 1021 (Building BCM)
Hanna Schmück
Wissenschaftliche Mitarbeiterin / Researcher
Lehrstuhl für Computerlinguistik
  • Room 1025 (Building BCM)
Georg Hofmann
Doktorand / PhD Student
Lehrstuhl für Computerlinguistik
  • Room 1021 (Building BCM)

Alumni

  • Dr. Jakob Prange

Publications

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OPAC:

2025 | 2024 | 2023

2025

Hanna Schmück, Michael Reder, Katrin Paula and Annemarie Friedrich. in press. A case study on annotating and analysing situation entity types in Reddit discussions on democracy.
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Paul Baker, Hanna Schmück and Yufang Qian. 2025. Automatic image tagging for corpus linguistics: a multimodal study of news representations of Islam. DOI: 10.1017/9781009581233
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Julian Lorenz, Mrunmai Phatak, Robin Sch?n, Katja Ludwig, Nico H?rmann, Annemarie Friedrich and Rainer Lienhart. in press. COPA-SG: dense scene graphs with parametric and proto-relations.
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Georg Hofmann and Annemarie Friedrich. 2025. Coling-UniA at GermEval 2025 shared task on candy speech detection: retrieval augmented generation for identifying expressions of positive attitudes in German YouTube comments.
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Christian Jaumann, Annemarie Friedrich and Rainer Lienhart. 2025. Coling-UniA at SciVQA 2025: few-shot example retrieval and confidence-informed ensembling for Multimodal Large Language Models. DOI: 10.18653/v1/2025.sdp-1.21
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Yejin Jung, Dana Gablasova, Vaclav Brezina and Hanna Schmück. 2025. Developing a coding scheme for annotating opinion statements in L2 interactive spoken English with application for language teaching and assessment. DOI: 10.32714/ricl.12.02.07
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Wei Zhou, Mohsen Mesgar, Annemarie Friedrich and Heike Adel. 2025. Efficient multi-agent collaboration with tool use for online planning in complex table question answering. DOI: 10.18653/v1/2025.findings-naacl.54
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Wei Zhou, Mohsen Mesgar, Annemarie Friedrich and Heike Adel. 2025. G-MACT at SemEval-2025 Task 8: exploring planning and tool use in question answering over tabular data.
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Valentin Knappich, Anna H?tty, Simon Razniewski and Annemarie Friedrich. 2025. PAP2PAT: benchmarking outline-guided long-text patent generation with patent-paper pairs. DOI: 10.18653/v1/2025.findings-acl.496
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Bolei Ma, Yuting Li, Wei Zhou, Ziwei Gong, Yang Janet Liu, Katja Jasinskaja, Annemarie Friedrich, Julia Hirschberg, Frauke Kreuter and Barbara Plank. 2025. Pragmatics in the era of large language models: a survey on datasets, evaluation, opportunities and challenges. DOI: 10.18653/v1/2025.acl-long.425
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Wei Zhou, Mohsen Mesgar, Heike Adel and Annemarie Friedrich. 2025. RITT: a Retrieval-assisted framework with Image and Text Table representations for table question answering. DOI: 10.18653/v1/2025.trl-1.8
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Hanna Schmück. in press. Sarah Buschfeld, Patricia Ronan, Theresa Neumaier, Andreas Weilinghoff and Lisa Westermayer (eds.), Crossing boundaries through corpora: Innovative corpus approaches within and beyond linguistics (Studies in Corpus Linguistics 119). Amsterdam and Philadelphia: John Benjamins, 2024. Pp vi + 265. ISBN 9789027215949 [Book Review]. DOI: 10.1017/s1360674325100439
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Wei Zhou, Mohsen Mesgar, Heike Adel and Annemarie Friedrich. 2025. Texts or images? A fine-grained analysis on the effectiveness of input representations and models for table question answering. DOI: 10.18653/v1/2025.findings-acl.117
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2024

Man Ho Ivy Wong and Jakob Prange. 2024. A Bayesian approach to (re)examining learning effects of cognitive linguistics–inspired instruction: a close replication of Wong, Zhao, and MacWhinney (2018). DOI: 10.1017/s0272263124000603
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Lukas Lange, Marc Müller, Ghazaleh Haratinezhad Torbati, Dragan Milchevski, Patrick Grau, Subhash Pujari and Annemarie Friedrich. 2024. AnnoCTR: a dataset for detecting and linking entities, tactics, and techniques in cyber threat reports.
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Wei Zhou, Mohsen Mesgar, Heike Adel and Annemarie Friedrich. 2024. FREB-TQA: a fine-grained robustness evaluation benchmark for Table Question Answering. DOI: 10.18653/v1/2024.naacl-long.137
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Steffen Kleinle, Jakob Prange and Annemarie Friedrich. 2024. OMoS-QA: a dataset for cross-lingual extractive question answering in a German migration context.
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Arcangelo Massari, Fabio Mariani, Ivan Heibi, Silvio Peroni and David Shotton. 2024. OpenCitations Meta. DOI: 10.1162/qss_a_00292
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Fabio Mariani, Max Koss and Lynn Rother. 2024. People information in provenance data: biographical entity linking with Wikidata and ULAN. DOI: 10.31664/zu.2024.114.07
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Timo Pierre Schrader, Lukas Lange, Simon Razniewski and Annemarie Friedrich. 2024. QUITE: quantifying uncertainty in natural language text in Bayesian reasoning scenarios. DOI: 10.18653/v1/2024.emnlp-main.153
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Hanna Schmück. 2024. Review of Dunn (2022): Natural Language Processing for Corpus Linguistics. Cambridge 新万博体育下载_万博体育app【投注官网】 Press. 84pp. [Book Review]. DOI: 10.1075/ijcl.00057.sch
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Tim Tarsi, Heike Adel, Jan Hendrik Metzen, Dan Zhang, Matteo Finco and Annemarie Friedrich. 2024. SciOL and MuLMS-Img: introducing a large-scale multimodal scientific dataset and models for image-text tasks in the scientific domain. DOI: 10.1109/wacv57701.2024.00450
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Maik Fr?be, Christopher Akiki, Timo Breuer, Thomas Eckart, Annemarie Friedrich, Lukas Gienapp, Jan Heinrich Merker, Martin Potthast, Harrisen Scells, Philipp Schaer and Benno Stein. 2024. Teaching information retrieval with a shared task across universities: first steps and findings.
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2023

Annemarie Friedrich, Nianwen Xue and Alexis Palmer. 2023. A kind introduction to lexical and grammatical aspect, with a survey of computational approaches. DOI: 10.18653/v1/2023.eacl-main.44
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Sophie Henning, William Beluch, Alexander Fraser and Annemarie Friedrich. 2023. A survey of methods for addressing class imbalance in deep-learning based natural language processing. DOI: 10.18653/v1/2023.eacl-main.38
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Jakob Prange and Emmanuele Chersoni. 2023. Empirical sufficiency lower bounds for language modeling with locally-bootstrapped semantic structures. DOI: 10.18653/v1/2023.starsem-1.40
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Lynn Rother, Fabio Mariani and Max Koss. 2023. Hidden value: provenance as a source for economic and social history. DOI: 10.1515/jbwg-2023-0005
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2023. LAW 2023: The 17th Linguistic Annotation Workshop (LAW-XVII) @ ACL 2023, proceedings of the workshop, July 13, 2023.
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Lynn Rother, Fabio Mariani and Max Koss. 2023. Linking (in)completeness: a collaborative approach to representing people in art provenance data. DOI: 10.5281/zenodo.8107371
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Timo Schrader, Teresa Bürkle, Sophie Henning, Sherry Tan, Matteo Finco, Stefan Grünewald, Maira Indrikova, Felix Hildebrand and Annemarie Friedrich. 2023. MuLMS-AZ: an argumentative zoning dataset for the materials science domain. DOI: 10.18653/v1/2023.codi-1.1
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Jakob Prange and Man Ho Ivy Wong. 2023. Reanalyzing L2 preposition learning with Bayesian mixed effects and a pretrained language model. DOI: 10.18653/v1/2023.acl-long.712
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Fabio Mariani, Lynn Rother and Max Koss. 2023. Teaching provenance to AI: an annotation scheme for museum data. DOI: 10.14361/9783839467107-014
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