Home  | News

07.12.2023

Teaser image to White Paper: Große Sprachmodelle entwickeln und anwenden

White Paper: Große Sprachmodelle entwickeln und anwenden

Check Out the New White Paper of the PLS Working Group Led by Volker Tresp

The current white paper from the PLS working group led by our PI Volker Tresp uses practical examples to illustrate the opportunities and challenges of language models and analyzes the conditions under which companies can leverage the potential of the technology with confidence and legal certainty.

The experts recommend the creation of an open, commercially usable data set in German that complies with European values and rules and supports the development of language models in Germany.

«From the perspective of AI research, LLMs represent a significant technological breakthrough. They unlock the intelligence of language. They enable solutions that were previously beyond the realm of technological possibilities, but now seem to be taken for granted.»
(V. Tresp)

#research #tresp
Subscribe to RSS News feed

Related

Link to Explaining AI Decisions: Shapley Values Enable Smart Exosuits

13.11.2025

Explaining AI Decisions: Shapley Values Enable Smart Exosuits

AI meets wearable robotics: MCML and Harvard researchers make exosuits smarter and safer with explainable optimization, presented at ECML-PKDD 2025.

Link to

10.11.2025

MCML at ICDM 2025

MCML researchers are represented with 2 papers at ICDM 2025.

Link to Research on human-centred Exosuit technology highlighted in Börsen-Zeitung

03.11.2025

Research on Human-Centred Exosuit Technology Highlighted in Börsen-Zeitung

Julian Rodemann worked with Harvard on interpretable algorithms for “Back Exosuits,” improving human–machine interaction.

Link to

02.11.2025

MCML at EMNLP 2025

MCML researchers are represented with 39 papers at EMNLP 2025 (18 Main, 13 Findings, and 8 Workshops).

Link to Language Shapes Gender Bias in AI Images

30.10.2025

Language Shapes Gender Bias in AI Images

Alexander Fraser shows AI image generators reproduce gender stereotypes differently across languages, highlighting the need for fair multilingual AI.

Back to Top