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Welcome to the Heidelberg Natural Language Processing Group

We aim to make machines understand language

Read more about our research
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NEWS

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New Publication

We present the new paper "An Annotated Dataset of Errors in Premodern Greek and Baselines for Detecting Them", by researchers from Princeton and MIT, with contributions from our own Frederick, accepted at NAACL'25 Findings.

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Celebrating the PhD Defense of Xiyan Fu

Xiyan's thesis "Understanding and Improving the Compositional Generalization Abilities of LLMs in Reasoning".
-- Congratulations, Xiyan, for your fine work!

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New Publication

We present our new paper "From Argumentation to Deliberation: Perspectivized Stance Vectors for Fine-grained (Dis)agreement Analysis", accepted at NAACL'25 Findings

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New Publication

We present our new paper "Do Vision & Language Decoders use Images and Text equally? How Self-consistent are their Explanations?", accepted at ICLR'25

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News Update from the HD-NLP group at ICL

News Update from the HD-NLP Group and collaborators with new new publications in the Journal of NLP and EMNLP 2024, as well as recent and upcoming talks!

Let's dive in!

Nov 23 We welcome Fabian Strobel to our group, as a new PhD student, affiliated with the Heidelberg Academy of Sciences, to work on Transliteration in Ancient Languages. Happy to have you on board, Fabian!
Sep 23 Letitia Parcalabescu will give keynote at LIMO 2023: Linguistic Insights from and for Multimodal Language Processing at KONVENS 2023 in Ingolstadt, about her research on Vision and Language Integration in Multimodal Machine Learning.
Sep 23 We are happy to announce our new publication Argument Quality Prediction for Ranking Documents, by Moritz Plenz, Raphael Buchmüller and Alexander Bondarenko. Accepted at Touché, CLEF 2023.
Sep 23 Frederick Riemenschneider presents his paper Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature at ALP 2023, the First Workshop on Ancient Language Processing in Varna, Bulgaria.
Aug 22 ACCEPT organized a Shared Task on Predicting Validity and Novelty of Arguments. Our report will be presented in the ArgMining Workshop 2022.

RESEARCH TEAM

TEAM

Group Leader

Anette Frank

Anette Frank

Prof. Dr.
Chair of Computational Linguistics
Email (click to copy)
Semantic NLP for advanced & situated Natural Language Understanding

Researchers

Moritz Plenz

Moritz Plenz

MSc Physics PhD Student Computational Linguistics
Email (click to copy)
Combining Knowledge Graphs and Language Models

Frederick Riemenschneider

MA Computational Linguistics BA Classical Philology (Greek)
Email (click to copy)
Low-resource Languages
Multilingual Language Models

Associated Researchers

Phillip Richter-Pechanski

BA Computational Linguistics PhD Student Computational Linguistics
Email (click to copy)
Information Extraction from Medical Texts
Institute for Computational Cardiology

Fabian Strobel

BA Computational Linguistics & Jewish Studies, Heidelberg MSc Digital Humanities, Leipzig PhD Student Computational Linguistics
Email (click to copy)
Transcription and Transliteration
Heidelberg Academy of Sciences

Student Assistants

Bohdana Ivakhnenko

BA Applied (Computational) Linguistics and English Language Student in MA Computational Linguistics, Heidelberg University
Email (click to copy)
Student Researcher in "AI & Translation"
Generation of Winograd Schemata and Knowledge Graphs for Cognitive Studies

“WE AIM
TO MAKE MACHINES
UNDERSTAND LANGUAGE.”

The main purpose of language is to encode and communicate information of all sorts.

Our research focuses on semantics — the study of meaning — and how a machine can assign meaning to utterances: words, sentences and texts, as humans can do. Our work is linguistically informed and applies advanced machine learning techniques.

Understanding of language requires knowledge of language and the world, the ability to perform reasoning, and situational context.
We study how to interface language with knowledge and how to ground language in the visual world. We investigate what can be left implicit in texts, given that language and knowledge interact, allowing humans to read between the lines.

For all this, humans and machines need knowledge:

about language, the world, people, social norms and the visual world.

“How do humans acquire and exchange knowledge?”
  • KNOWLEDGE-BASED LANGUAGE PROCESSING
  • MACHINE READING COMPREHENSION
  • COMMONSENSE INFERENCE IN SOCIAL SITUATIONS
  • COMPUTATIONAL ARGUMENTATION
“And how to express thoughts in language — accurately and naturally?”
  • NATURAL LANGUAGE GENERATION
  • MEANING-BASED NLG EVALUATION METRICS
  • RECONSTRUCTING IMPLICIT KNOWLEDGE IN TEXT
“How to represent the meaning of a discourse?”
  • STRUCTURED MEANING REPRESENTATIONS
  • REPRESENTING EVENTS AND THEIR PARTICIPANTS
  • RESOLVING ANAPHORA
“How do humans communicate in a visual situation?”
  • MULTIMODAL LANGUAGE PROCESSING
  • GROUNDING LANGUAGE IN IMAGES

PUBLICATIONS

PAPER

2025
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Do Vision & Language Decoders use Images and Text equally? How Self-consistent are their Explanations?

Parcalabescu, L., Frank, A. (2025)

Proceedings of The Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore, China.

From Argumentation to Deliberation: Perspectivized Stance Vectors for Fine-grained (Dis)agreement Analysis

Plenz, M., Heinisch, P., Gehring, J., Cimiano, P., Frank, A. (2025)

Findings of the Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025) , Albuquerque, New Mexico.

An Annotated Dataset of Errors in Premodern Greek and Baselines for Detecting Them

Brooks, C., Haubold, J., Cowen-Breen, C., White, J., DeVaul, D., Riemenschneider, F., Narasimhan, K., Graziosi, B. (2025)

Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico.

Beyond Base Predictors: Using LLMs to Resolve Ambiguities in Akkadian Lemmatization

Riemenschneider, F. (2025)

Proceedings of the Second Workshop on Ancient Language Processing, The Albuquerque Convention Center, Laguna.
2024
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On Measuring Faithfulness or Self-consistency of Natural Language Explanations

Parcalabescu, L., Frank, A. (2024)

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) .

ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models

Kesen, I., Pedrotti, A., Dogan, M., Cafagna, M., Acikgoz, E., Parcalabescu, L., Calixto, I., Frank, A., Gatt, A., Erdem, A., Erdem, E. (2024)

Proceedings of The Twelfth International Conference on Learning Representations (ICLR 2024).

Graph Language Models

Plenz, M., Frank, A. (2024)

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) .

Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical Transformers

Riemenschneider, F., Krahn, K. (2024)

Proceedings of the 6th Workshop on Research in Computational Linguistic Typology and Multilingual NLP, St. Julian's, Malta.

PAKT: Perspectivized Argumentation Knowledge Graph and Tool for Deliberation Analysis

Plenz, M., Heinisch, P., Frank, A., Cimiano, P. (2024)

Proceedings of the 1st International Conference on Recent Advances in Robust Argumentation Machines (RATIO-24) .

Exploring Continual Learning of Compositional Generalization in NLI

Fu, X., Frank, A. (2024)

Transactions of the Association for Computational Linguistics.

Compositional Structured Explanation Generation with Dynamic Modularized Reasoning

Fu, X., Frank, A. (2024)

Proceedings of the 13th Joint Conference on Lexical and CompuProceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico.

Building Bridges. Reconstructing Implicit Information in Argumentative Texts Using Commonsense Knowledge.

Becker, M. (2024)

Mannheim.

Robust Argumentation Machines. First International Conference, RATIO 2024, Bielefeld, Germany, June 5–7, 2024, Proceedings

(2024)

The Mystery of Compositional Generalization in Graph-based Generative Commonsense Reasoning

Fu, X., Frank, A. (2024)

Findings of the Association for Computational Linguistics: EMNLP 2024, Miami, Florida, USA.

Clinical information extraction for Low-resource languages with Few-shot learning using Pre-trained language models and Prompting

Richter-Pechanski, P., Wiesenbach, P., Schwab, D., Kiriakou, C., Geis, N., Dieterich, C., Frank, A. (2024)

Natural Language Processing.
2023
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SETI: Systematicity Evaluation of Textual Inference

Fu, X., Frank, A. (2023)

Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada.

SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph Distance

Opitz, J., Meier, P., Frank, A. (2023)

Proceedings of the 15th International Conference on Computational Semantics (IWCS 2023) , Nancy, France.

AMR4NLI: Interpretable and robust NLI measures from semantic graphs

Opitz, J., Wein, S., Steen, J., Frank, A., Schneider, N. (2023)

Proceedings of the 15th International Conference on Computational Semantics (IWCS 2023), Nancy, France.

MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks

Parcalabescu, L., Frank, A. (2023)

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL’23), Toronto, Canada.

Similarity-weighted Construction of Contextualized Commonsense Knowledge Graphs for Knowledge-intense Argumentation Tasks

Plenz, M., Opitz, J., Heinisch, P., Cimiano, P., Frank, A. (2023)

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Toronto, Canada.

Exploring Large Language Models for Classical Philology

Riemenschneider, F., Frank, A. (2023)

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL’23), Toronto, Canada.

Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature

Riemenschneider, F., Frank, A. (2023)

Proceedings of the Ancient Language Processing Workshop, Varna, Bulgaria.

PROJECTS

2025
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AI & Translation: Comparing cognitive processes in the human brain to AI models – using the learning conditions of interpreters as a testing ground (2025 -- 2026)

AI & Translation: Comparing cognitive processes in the human brain to AI models – using the learning conditions of interpreters as a testing ground (2025 -- 2026)

A joint project between Interpreting Science, Computational Linguistics and Neuroscience, aiming to Comparing cognitive processes in the human brain to AI models – using the learning conditions of interpreters as a testing ground.
2024
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RAGE – Roman and Greek Emotions. A quantitative approach to emotions in classical philology

RAGE – Roman and Greek Emotions. A quantitative approach to emotions in classical philology

A joint project between Computational Linguistics and Classical Philology joining forces for the analysis of Emotions in classical Roman and Ancient Greek literary texts.

2021
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ACCEPT: Perspectivized Argument Knowledge Graphs for Deliberation Support (2021 – 2024)

ACCEPT: Perspectivized Argument Knowledge Graphs for Deliberation Support (2021 – 2024)

Joint project between Prof. Anette Frank (ICL, Heidelberg University) and Prof. Philipp Cimiano (University of Bielefeld) within the DFG priority program RATIO: Robust Argumentation Machines

RELEASES

DATA

CODE

GitHub

Find our latest code on GitHub

You can find our latest code releases on our Heidelberg-NLP Github page!

Over 23 repositories containing code related to our recent publications.

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