Lecturer: Barbara Plank
Fields: Artificial Intelligence, Natural Language Processing
Content
Despite the recent success of Natural Language Processing (NLP) driven by advances in large language models (LLMs), there are many challenges ahead to make NLP more trustworthy. In this course, we will look at trustworthiness by taking the lens of uncertainty in language, from uncertainty in inputs, in outputs and how models deal with uncertainty themselves.
Literature
- Litschko, Müller-Eberstein, van der Goot, Weber-Genzel, Plank (2023). Establishing Trustworthiness: Rethinking Tasks and Model Evaluation. https://aclanthology.org/2023.emnlp-main.14/
- Baan, Daheim, Ilia, Ulmer, Li, Fernández, Plank, Sennerich, Zerva, Aziz (2023). Uncertainty in Natural Language Generation: From Theory to Applications. https://arxiv.org/pdf/2307.15703
Lecturer
Barbara Plank is Professor and co-director of the Center for Information and Language Processing at LMU Munich. She holds the Chair for AI and Computational Linguistics at LMU where she leads the MaiNLP research lab (Munich AI and NLP lab, pronounced “my NLP”). Her lab focuses on robust machine learning for Natural Language Processing with an emphasis on human-inspired and data-centric approaches.
Affiliation: LMU Munich
Homepage: https://bplank.github.io/