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There is increasing interest in understanding multilingual training dynamics and shared representations, instead of analysing final model checkpoints. Tracing training dynamics allows us to analyse when linguistic information and shared concept spaces emerge during pre-training and understand model mechanisms, e.g. where alignment breaks down. In this talk, I will discuss why studying training dynamics is useful, particularly from a multilingual lens, and present recent findings on studying model behaviour and representations during pre-training.
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 Munich and is a visiting Professor at the Computer Science department at the IT University of Copenhagen. Her MaiNLP research lab (Munich AI and NLP lab) focuses on robust machine learning for Natural Language Processing with an emphasis on human-inspired and data-centric approaches. Her research has been funded by distinguished grants and awards, including an ERC Consolidator Grant, DFF Sapere Aude Research Leader grant, ELLIS Fellow, and several best paper awards. She regularly serves on international committees, including the Association for Computational Linguistics (ACL), the European Chapter of the ACL, the Northern European Association for Language Technology (NEALT) and Scientific Advisory Boards of Research Centers across Europe.
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