Welcome to the first workshop on Multimodal Representation Learning (MRL), subtitled Perks and Pitfalls. The workshop takes place virtually as part of ICLR 2023 on May 5, 2023.
About the workshop
Following deep learning, multimodal machine learning has made steady progress, becoming ubiquitous in many domains. Learning representations from multiple modalities can be beneficial since different perceptual modalities can inform each other and ground abstract phenomena in a more robust, generalisable way. However, the complexity of different modalities can hinder the training process, requiring careful design of the model in order to learn meaningful representations. In light of these seemingly conflicting aspects of multimodal learning, we must improve our understanding of what makes each modality different, how they interact, and what are the desiderata of multimodal representations. With this workshop, we aim to bring the multimodal community together, promoting work on multimodal representation learning that provides systematic insights into the nature of the learned representations, as well as ways to improve and understand the training of multimodal models, both from a theoretical and empirical point of view.
- Paper submission start: December 20, 2022, 23:59 AoE.
- Paper submission deadline: February 3, 2023, 23:59 AoE.
- Notification to authors: March 5, 2023, 23:59 AoE.
- Camera-ready version: TBA.
- Workshop date: May 5, 2023.
Contact us at firstname.lastname@example.org. All dates are subject to change.