Causality and Large Models

Our workshop aims to explore the synergies between causality and large models, also known as ``foundation models,'' which have demonstrated remarkable capabilities across multiple modalities (text, images, audio, etc.). Despite their high performance, the opaque nature of these large models raises crucial questions regarding their trustworthiness, especially in safety-critical domains. A growing community of researchers is turning towards a more principled framework to address these concerns, better understand the behavior of large models, and improve their reliability: causality.Specifically, this workshop will focus on four directions: causality in large models, to assess their causal reasoning abilities, causality for improving large models, causality with large models to enhance causal inference and discovery methods, and causality of large models to understand and control their internal mechanisms. The invited speakers and panelists (almost all of which have already been confirmed to attend) represent a diverse set of perspectives and expertise, across both academia and industry.The workshop is organized by a team of 12 members from six different institutions across North America, Europe, and Asia, ensuring diversity across research interests, backgrounds, and demographics. Visit our website: https://calm-workshop-2024.github.io/