Machine Learning Group – Prof. Dr. Alan Akbik
Our group focuses on research in machine learning (ML) and natural language processing (NLP). We aim to give machines the ability to understand and use human language. To achieve this, our group develops the Flair framework for automated text analysis. It is already used in hundreds of research projects and industrial applications and is frequently listed among the most popular deep learning frameworks for NLP.
On these pages you can find more information about our group:
Open positions!
Our group is growing quickly thanks to many DFG projects and industrial collaborations, so we are always looking for PhD candidates and student assistants to join our group. Contact us in case of interest!
News
- 08.10.2023 - New Paper: Our full paper "CleanCoNLL: A Nearly Noise-Free Named Entity Recognition Dataset" accepted to EMNLP 2023!
- 30.09.2023 - New Paper: Our paper "Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs" accepted to EMNLP 2023: System Demonstrations!
- 08.09.2023 - OpinionGPT v2: Our new version of OpinionGPT now models explicit biases for English that you can select in our web demo! Details in our paper!
- 10.07.2023 - Outstanding Reviewer Award: Our group wins Outstanding Reviewer Award at ACL 2023
- 11.05.2023 - OpinionGPT: Our German-langauge OpinionGPT now available as web demo!
- 05.05.2023 - Outstanding Paper Award: Our paper "ZELDA: A Comprehensive Benchmark for Supervised Entity Disambiguation" wins Outstanding Paper Award at EACL 2023!
- 15.04.2023 - New Release: New Website on Flair documentation!
- 30.03.2023 - Open Source Release: New version of Flair (v0.12.2) released!
- 20.02.2023 - Open Source Release: Our ZELDA Entity Linking dataset now available on Github!
- 10.01.2023 - New Paper: Full paper on entity linking accepted to EACL 2023!