Large Language Models for structured data
Paolo Papotti | 3IA Chairholder
We focus on addressing the limitations of Large Language Models (LLMs) in handling structured data, which hinders their adoption for data-centric tasks like analyzing large tabular datasets. We aim to develop novel frameworks and architectures for encoding structured data into LLMs, thereby enabling complex table understanding capabilities in pre-trained models.
No demos available for this chair
