HIDA Lecture: Efficient Natural Language Processing
Speaker: Simon Ostermann, German Research Center for Artificial Intelligence (DFKI)
Date: 25.11.2024, 11:00 am
Title: A short Introduction to Efficient Natural Language Processing
Abstract
This talk will outline the challenges of developing efficient models with limited data and resources. It will explore strategies to maximise data and model efficiency, emphasising the importance of managing large models that typically require significant computational resources and are predominantly trained on English data.
It will also discuss techniques like pre-filtering, online methods, data augmentation, and curriculum learning, as well as parameter-efficient training methods like adapters, prompt tuning, and prefix tuning to enhance model performance without extensive data requirements.
Simon Ostermann
Simon Ostermann is a computational linguist and Senior Researcher at the German Research Center for Artificial Intelligence (DFKI), where he leads a research group on Efficient and Explainable Natural Language Processing in the lab for Multilinguality and Language Technology. His research interests are on trying to improve the accessibility of Large Language Models (LLMs) in several aspects. First, by making the parameters and behaviour or LLMs more explainable and understandable to both end users and researchers, second, by improving language models in terms of their data consumption and size.
