SpecialityIstituto di Linguistica Computazionale - CNR, Pisa, IT

Opening Large Language ModelsAs language models become increasingly complex and sophisticated, the processes leading to their predictions are growing increasingly difficult to understand. Research in NLP interpretability focuses on explaining the rationales driving model predictions and is crucial for building trust and transparency in the usage of these systems in real-world scenarios. In this talk, we will first introduce state-of-the-art Neural Language Models (NLMs) and discuss their characteristics. Then we will cover the most commonly applied analysis methods for understanding the inner behaviour of NLMs based on Transformer architectures and how they implicitly encode linguistic knowledge.