International Workshop on Multimodal Learning – 2023 Theme: Multimodal Learning with Foundation Models

Chandan Reddy

Abstract

The recent advancements in machine learning and artificial intelligence (particularly foundation models such as BERT, GPT-3, T5, ResNet, etc.) have demonstrated remarkable capabilities and driven significant revolutionary changes to the way we make inferences from complex data. These models represent a fundamental shift in the way data are approached and offer exciting new research directions and opportunities for multimodal learning and data fusion. Given the potential of foundation models to transform the field of multimodal learning, there is a need to bring together experts and researchers to discuss the latest developments in this area, exchange ideas, and identify key research questions and challenges that need to be addressed. By hosting this workshop, we aim to create a forum for researchers to share their insights and expertise on multimodal data fusion and learning using foundation models, and to explore potential new research directions and applications in the rapidly evolving field. We expect contributions from interdisciplinary researchers to study and model interactions between (but not limited to) modalities of language, graphs, time-series, vision, tabular data, sensors, and more. Our workshop will emphasize interdisciplinary work and aim at seeding cross-team collaborations around new tasks, datasets, and models.

Yuan Ling, Fanyou Wu, Shujing Dong, Yarong Feng, George Karypis, Chandan K. Reddy: International Workshop on Multimodal Learning – 2023 Theme: Multimodal Learning with Foundation Models. KDD 2023: 5868-5869