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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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Three new publications at AACL, EMNLP and Eval4NLP

from our team and collaborators on:
SBERT studying Meaning Representations, New challenges for AMR parsing metrics, and Adapter-based Fine-tuning in V&L models.
Congratulations to all authors!

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New publication from the Heidelberg NLP group

We announce a new publication at *SEM 2022 at NAACL, on
A Dynamic, Interpretable CheckList for Meaning-oriented NLG Metric Evaluation – through the Lens of Semantic Similarity Rating. Congratulations to all authors!

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Another successful PhD Defense, by Debjit Paul

We are celebrating the PhD defense of Debjit Paul, for his thesis on Social Commonsense Reasoning. Congratulations, Dr. Paul!

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Neural Natural Language Generation: Multilinguality, Multimodality, Controllability and Learning

A survey by members of the COST Action Multi3Generation: Multi-task, Multilingual, Multi-modal, to appear in JAIR

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VALSE 💃 accepted @ACL 2022 Main

Our paper VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena was accepted at ACL 2022 Main.

Aug 22 ACCEPT organized a Shared Task on Predicting Validity and Novelty of Arguments. Our report will be presented in the ArgMining Workshop 2022.
July 22 Laura Zeidler presents our work on using CheckList to evaluate textual, graph-based and contextualized NLG evaluation metrics through the lens of Semantic Similarity Rating, in the *SEM Conference at NAACL 2022 in Seattle.
Apr 22 Letitia Parcalabescu and Juri Opitz will present their newest work in the upcoming ACL Meeting in Dublin: VALSE and Weisfeiler Leman in the Bamboo .
Dec 21 The paper: Weisfeiler-Leman in the BAMBOO: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity, by Juri Opitz, Angel Daza and Anette Frank has now appeared in Transactions of the ACL.
Nov 21 Anette Frank gives a panelist talk in the ArgMining Workhop 2021.

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

Xiyan Fu

Xiyan Fu

MSc Computer Science PhD Student Computational Linguistics
Email (click to copy)
Event-based Reasoning
Natural Language Generation
Structured Meaning Representation
Juri Opitz

Juri Opitz

MA Computational Linguistics PhD Student Computational Linguistics
Email (click to copy)
Meaning representations
Explainability
Argument Mining
Letitia Parcalabescu

Letitia Parcalabescu

MSc Physics PhD Student Computational Linguistics
Email (click to copy)
Multimodal Learning
Vision and Language
Multimodal Understanding
Moritz Plenz

Moritz Plenz

MSc Physics PhD Student Computational Linguistics
Email (click to copy)
Argument Knowledge Graphs
ACCEPT

Frederick Riemenschneider

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

Associated Researchers

Andrea Pedrotti

Andrea Pedrotti

Master of Science in Digital Humanities PhD Student in Computer Science
Email (click to copy)
Multimodal Deep Learning
Multilingual Embeddings
Transfer Learning

Phillip Richter-Pechanski

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

“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

2022
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MAGMA – Multimodal Augmentation of Generative Models through Adapter-based Finetuning

Eichenberg, C., Black, S., Weinbach, S., Parcalabescu, L., Frank, A. (2022)

Findings of EMNLP.

Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning

Erdem, E., Kuyu, M., Yagcioglu, S., Frank, A., Parcalabescu, L., Plank, B., Babii, A., Turuta, O., Erdem , A., Calixto, I., Lloret, E., Apostol, E., Truica, C., Sandrih, B., Gatt, A., Martincic-Ipsic, S., Berend, G., Korvel , G. (2022)

Journal of Artificial Intelligence Research (JAIR), 1131-1207

Strategies for Framing Argumentative Conclusion Generation

Heinisch, P., Frank, A., Opitz, J., Cimiano , P. (2022)

Proceedings of the 15th International Natural Language Generation Conference.

Data Augmentation for Improving the Prediction of Validity and Novelty of Argumentative Conclusions

Heinisch, P., Plenz, M., Opitz, J., Frank, A., Cimiano, P. (2022)

Proceedings of the 9th Workshop on Argument Mining (ArgMining), Online and in Gyeongju, Republic of Korea, 19-33

Overview of the 2022 Validity and Novelty Prediction Shared Task

Heinisch, P., Frank, A., Opitz, J., Plenz, M., Cimiano, P. (2022)

Proceedings of the 9th Workshop on Argument Mining (ArgMining), Online and in Gyeongju, Republic of Korea, 84-94

Better Smatch = Better Parser? AMR evaluation is not so simple anymore

Opitz, J., Frank, A. (2022)

Proceedings of the 3rd Workshop on Evaluation & Comparison of NLP Systems (Eval4NLP 2022) ,co-located at AACL 2022, 32-43

SBERT studies Meaning Representations: Decomposing Sentence Embeddings into Explainable Semantic Features

Opitz, J., Frank, A. (2022)

Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP 2022), Online, 625-638

VALSE💃: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena

Parcalabescu, L., Cafagna, M., Muradjan, L., Frank, A., Calixto, I., Gatt, A. (2022)

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 8253-8280

A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation – through the Lens of Semantic Similarity Rating

Zeidler, L., Opitz, J., Frank, A. (2022)

Proceedings of the 11th Joint Conference on Lexical and Computational Semantics (*SEM), 157-172
2021
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COCO-EX: A Tool for Linking Concepts from Texts to ConceptNet

Becker, M., Korfhage, K., Frank, A. (2021)

Proceedings of the Software Demonstrations of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021), 119-126

Reconstructing Implicit Knowledge with Language Models

Becker, M., Liang, S., Frank, A. (2021)

Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures at NAACL 2021, 11-24

CO-NNECT: A Framework for Revealing Commonsense Knowledge Paths as Explicitations of Implicit Knowledge in Texts

Becker, M., Korfhage, K., Paul, D., Frank, A. (2021)

Proceedings of the 14th International Workshop on Computational Semantics (IWCS), Groningen, The Netherlands (Online), 21-32

Weisfeiler-Leman in the BAMBOO: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity

Opitz, J., Daza, A., Frank, A. (2021)

Transactions of the Association for Computational Linguistics (TACL), 1425-1441

Explainable Unsupervised Argument Similarity Rating with Abstract Meaning Representation and Conclusion Generation

Opitz, J., Heinisch, P., Wiesenbach, P., Cimiano, P., Frank, A. (2021)

Proceedings of the Eighth Argument Mining Workshop, Punta Cana, Dominican Republic, 24-35

Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR

Opitz, J., Frank, A. (2021)

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021), Online, 1504-1518

What is Multimodality?

Parcalabescu, L., Trost, N., Frank, A. (2021)

Proceedings of the First Workshop on Multimodal Semantic Representations (MMSR), Groningen, The Netherlands (Online), 1-10

Seeing Past Words: Testing the Cross-Modal Capabilities of Pretrained V&L Models

Parcalabescu, L., Gatt, A., Frank, A., Calixto, I. (2021)

Proceedings of the First Workshop on Multimodal Semantic Representations (MMSR), Groningen, The Netherlands (Online), 32-44

COINS: Dynamically Generating COntextualized Inference Rules for Narrative Story Completion

Paul, D., Frank, A. (2021)

Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) , Online, 5086-5099

Generating Hypothetical Events for Abductive Inference

Paul, D., Frank, A. (2021)

Proceedings of The Tenth Joint Conference on Lexical and Computational Semantics (*SEM 2021), Online, 67-77

Grounding Plural Phrases: Countering Evaluation Biases by Individuation

Suter, J., Parcalabescu, L., Frank, A. (2021)

Proceedings of the 2nd Workshop on Advances in Language and Vision Research (ALVR 2021) at NAACL 2021, Online, 22-28

Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing

Uhrig, S., Garcia, Y., Opitz, J., Frank, A. (2021)

Proceedings of the 17th International Conference on Parsing Technologies and the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (IWPT 2021), Online, 58-64
2020
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Implicit Knowledge in Argumentative Texts: An Annotated Corpus

Becker, M., Korfhage, K., Frank, A. (2020)

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC), Marseille, France, 2316-2324

Explaining Arguments with Background Knowledge -- Towards Knowledge-based Argumentation Analysis

Becker, M., Hulpus, I., Paul, D., Opitz, J., Kobbe, J., Stuckenschmidt, H., Frank, A. (2020)

Datenbank Spektrum (Special Issue: Argumentation Intelligence), 131-141

X-SRL: A Parallel Cross-Lingual Semantic Role Labeling Dataset

Daza, A., Frank, A. (2020)

The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), Online, 3904-3914

Neural Reranking for Dependency Parsing: An Evaluation

Do, B., Rehbein, I. (2020)

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), Online, 4123-4133

Parsers Know Best: German PP Attachment Revisited

Do, B., Rehbein, I. (2020)

Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), Barcelona, Spain (Online), 2049-2061

Herausforderungen Maschinellen Sprachverstehens. Algorithmus für Kreativität gesucht

Frank, A., Markert, K. (2020)

Ruperta Carola Forschungsmagazin, 86-95

AMR Quality Rating with a Lightweight CNN

Opitz, J. (2020)

Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, Suzhou, China, 235-247

AMR Similarity Metrics from Principles

Opitz, J., Parcalabescu, L., Frank, A. (2020)

Transactions of the Association for Computational Linguistics, 522-538

Exploring Phrase Grounding without Training: Contextualisation and Extension to Text-Based Image Retrieval

Parcalabescu, L., Frank, A. (2020)

Proceedings of the Workshop on Multimodal Learning (In conjunction with CVPR 2020), Seattle, WA, USA.

Argumentative Relation Classification with Background Knowledge.

Paul, D., Opitz, J., Becker, M., Kobbe, J., Hirst, G., Frank, A. (2020)

Proceedings of the 8th International Conference on Computational Models of Argument (COMMA 2020), 319-330

Social Commonsense Reasoning with Multi-Head Knowledge Attention

Paul, D., Frank, A. (2020)

In Findings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2969-2980

PROJECTS

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

2018
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ExpLAIN: Between the Lines – Knowledge-based Analysis of Argumentation in a formal Argumentation
Inference System (2018 – 2021)

ExpLAIN: Between the Lines – Knowledge-based Analysis of Argumentation in a formal Argumentation Inference System (2018 – 2021)

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

The project will uncover missing explanatory links in argumentative texts, fill in automatically acquired knowledge that makes the structure of the argument explicit and establish and verify the knowledge-enhanced argumentation structure with a combination of formal reasoning and machine learning.

Go to project page
2015
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DFG-Graduiertenkolleg AIPHES „Adaptive Informationsaufbereitung aus heterogenen Quellen“ (2015 – 2021)

DFG-Graduiertenkolleg AIPHES „Adaptive Informationsaufbereitung aus heterogenen Quellen“ (2015 – 2021)

The interdisciplinary research training group AIPHES was launched in April 2015. In a three-year program, 11 PhD candidates, as well as postdoctoral researchers and associated researchers will collaborate under the guiding theme of multi-document summarization of heterogeneous resources. Go to project page
Leibniz ScienceCampus "Empirical Linguistics and Computational Language Learning" (2015 – 2020)

Leibniz ScienceCampus "Empirical Linguistics and Computational Language Learning" (2015 – 2020)

The Leibniz ScienceCampus “Empirical Linguistics and Computational Language Modeling” aims to conduct innovative research to support the high-quality automatic annotation of large-scale corpus resources of German language through induction of domain-, genre- and variety-adaptive natural language processing models, to enable advanced empirical research in linguistics as well as innovative applications in the humanities and the social sciences. Go to project page

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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