Stockholm university

Research group Natural Language Processing Research Group

The Natural Language Processing Research Group develops, applies and evaluates NLP methods, in particular involving large language models, across various domains. We focus on topics such as privacy, explainability, and domain adaptation.

HPV-16 cells - a high-risk type for cancer.
The research group works with different types of data, healthcare data is one example. Photo: National Cancer Institute/Unsplash.

The Natural Language Processing Research Group carries out research on topics concerning methods for processing, modeling and analyzing text, including large language models (LLMs). We are motivated by real-world applications of Natural Language Processing (NLP) in domains such as healthcare, education, and security.

We have built up extensive expertise in clinical NLP for analyzing healthcare data and, to that end, have a research infrastructure called Health Bank. Clinical NLP methods enable automatic large-scale analysis of healthcare data and are valuable for improving healthcare, for example by building clinical prediction models that incorporate information from clinical notes. We explore how LLMs can be used in healthcare and apply domain adaptation for creating clinical language models, especially using privacy-preserving NLP methods (such as de-identification or synthetic training data).

Another focus application area is education, where we are interested in using pre-trained language models for different educational use cases – automated essay scoring, question answering/generation and educational content recommendation – to enhance teaching and learning processes. To enable development of intelligent and adaptive learning systems, we explore techniques such as retrieval-augmented generation (RAG) and tool-augmented generation (TAG).

Security is another application area where our focus is on detection and analysis of online harms such as hate speech, threats, and violent extremist content. We are also interested in threat assessment of written communication and to determine the seriousness of threats. We host the European Online Hate Lab, a hub for researchers and organisations that detect and analyse online hate.

Furthermore, explainability is critical for the development of trustworthy AI, therefore we develop methods for explainable NLP, especially in relation to LLMs. We focus especially, but not exclusively, on developing NLP methods for the Swedish language.

Group members

Group managers

Hercules Dalianis

Professor

Department of Computer and Systems Sciences
Hercules Dalianis

Aron Henriksson

Associate professor

Department of Computer and Systems Sciences
Aron Henriksson

Members

Tony Lindgren

Unit head SAS

Department of Computer and Systems Sciences
Tony Lindgren

Martin Duneld

Universitetslektor

Department of Computer and Systems Sciences

Eriks Sneiders

Universitetslektor

Department of Computer and Systems Sciences
Eriks Sneiders

Lisa Kaati

Universitetslektor

Department of Computer and Systems Sciences
Lisa Kaati

Amin Jalali

Associate Professor

Department of Computer and Systems Sciences
Amin Jalali

Workneh Yilma Ayele

Utbildningsassistent

Department of Computer and Systems Sciences

Andrea Andrenucci

Studievägledare, Studierektor grundnivå och avancerad nivå

Department of Computer and Systems Sciences

Eric Svee

Universitetslektor

Department of Computer and Systems Sciences
Eric-Oluf Svee

Xiu Li

Teaching assistant

Department of Computer and Systems Sciences
Xiu Li

Yongchao Wu

Doktorand

Department of Computer and Systems Sciences
yongchao

Thomas Vakili

PhD student

Department of Computer and Systems Sciences
Thomas_Vakili_2022

Korbinian Robert Randl

PhD student

Department of Computer and Systems Sciences
Korbinian Randl

Lukas Lundmark

PhD student

Department of Computer and Systems Sciences

Martin Hansson

Amanuens

Department of Computer and Systems Sciences
Porträttbild Martin Hansson, DSV

Ioannis Pavlopoulos

Affiliated researcher

Department of Computer and Systems Sciences
John (Ioannis) Pavlopoulos

Research projects

Publications

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