The Paradigm Shift: From Rules to Models in Natural Language Processing

Summer School Overview

Natural Language Processing has witnessed a clear paradigm shift from rule-based approaches to data-driven language models. While Deep Learning and Large Language Models have transformed the field, practical experience shows that model-based systems do not always outperform classical rule-based methods in every setting.

This summer school addresses that transition through an intensive 3-day programme that combines theoretical foundations with practical sessions. Core topics include LLMs, explainability, datasets and bias, low-resource languages, machine translation, sentiment analysis, model optimisation, and eye-tracking/gaze data for NLP.

The school is intended for newcomers and experienced participants in NLP, computer science, data science, cybersecurity, corpus linguistics, and related language-technology disciplines.