Frederick Riemenschneider and Kevin Krahn won the constrained subtask of the SIGTYP 2024 shared task.
Letitia Parcalabescu gave an invited talk about her work at heidelberg.ai at the DKFZ.
Former ICL student Laura Zeidler won the GSCL Best Thesis Award for her BA Thesis: “An Interpreted Dynamic Testsuite for the Evaluation of Semantic Similarity Metrics used in Parsing and Generation”. Congratulations!
We are happy to announce six new publications, with partners and colleagues, to be presented in Toronto in July.
Congratulations to all authors!
We celebrate the successful PhD defense of Juri Opitz, for his thesis on Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search. Congratulations!
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| Semantic NLP for advanced & situated Natural Language Understanding |
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Event-based Reasoning Natural Language Generation Structured Meaning Representation |
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Multimodal Learning Vision and Language Multimodal Understanding |
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Argument Knowledge Graphs ACCEPT |
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Low-resource Languages Multilingual Language Models |
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| Information Extraction from Medical Texts | |
| Institute for Computational Cardiology |
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| Heidelberg Academy of Sciences |
| Email (click to copy) | Heidelberg University |
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.
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
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
You can find our latest code releases on our Heidelberg-NLP Github page!
Over 23 repositories containing code related to our recent publications.
