Machine Learning Group – Prof. Dr. Alan Akbik
Welcome to the Machine Learning Group of the Humboldt-Universität zu Berlin!
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:
Flair
The Flair framework for state-of-the-art NLP
Our research
Transfer learning, universal representations, etc.
Our teaching
Information on courses for students
Open PhD Position!
We have a new PhD position available, fully funded for 4 years through the HEIBRIDS programme!
- Apply here! Deadline is August 23rd!
News
- 01.07.2024 - New lab member: Dr. Pieter Delobelle -expert for Dutch-language LLMs (and beyond)- joins us as visiting researcher. Welcome to Berlin! We look forward to working together on Dutch/German/English LLMs!
- 01.07.2024 - Senior Area Chair (ACL 2025): Prof. Akbik named as Senior Area Chair for Language Modeling at ACL 2025!
- 04.06.2024 - New paper (ACL 2024): Our demo paper "Fundus: A Simple-to-Use News Scraper Optimized for High Quality Extractions" accepted to ACL 2024!
- 16.05.2024 - New paper (ACL 2024): Our paper "Choose Your Transformer: Improved Transferability Estimation of Transformer Models on Classification Tasks" accepted to ACL 2024!
- 14.05.2024 - New paper: Our paper "NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition" now on ArXiv!
- 05.04.2024 - New research grant (IBB): The Investitionsbank Berlin (IBB) approved a new research grant for a Forschungstransfer project to industry partner PIKK Systems!
- 27.03.2024 - New startup grant: The German Federal Ministry for Economic Affairs (BMWK) approved an EXIST startup grant for FactorizeBio!
- 25.03.2024 - New paper: "Fundus: A Simple-to-Use News Scraper Optimized for High Quality Extractions" now on ArXiv!
- 21.03.2024 - New paper (NAACL 2024): Our paper "OpinionGPT: Modelling Explicit Biases in Instruction-Tuned LLMs" accepted to NAACL 2024: System Demonstrations!
- 13.03.2024 - New paper (NAACL 2024): Our paper "BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models" accepted to NAACL 2024!
- 01.03.2024 - New research grant (BMBF): The German Federal Ministry of Education and Research (BMBF) approved a new research grant for a 3-year project together with industry partner dida Datenschmiede!
- 22.02.2024 - New paper: Our paper "HunFlair2 in a cross-corpus evaluation of named entity recognition and normalization tools" now on ArXiv!
- 20.02.2024 - New paper (COLING 2024): Our paper "PECC: Problem Extraction and Coding Challenges" accepted to COLING 2024!
- 31.01.2024 - New paper: Our paper "SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity" now on ArXiv!
- 18.01.2024 - Two new papers (EACL 2024): Our full papers "Large-Scale Label Interpretation Learning for Few-Shot Named Entity Recognition" and "Parameter-Efficient Fine-Tuning: Is There An Optimal Subset of Parameters to Tune?" accepted to EACL 2024!