[2024 Best AI Paper] A Practitioner's Guide to Continual Multimodal Pretraining

By Paper With Video

Community Score: 50% | 119 views | 1y

0 community ratings: null thumbs up, null thumbs down

This video was created using https://paperspeech.com. If you’d like to create explainer videos for your own papers, please visit the website! Title: A Practitioner's Guide to Continual Multimodal Pretraining Authors: Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier Hénaff, Samuel Albanie, Matthias Bethge, Zeynep Akata Abstract: Multimodal foundation models serve numerous applications at the intersection of vision and language. Still, despite being pretrained on extensive data, they become outdated over time. To keep models updated, research into continual pretraining mainly explores scenarios with either (1) infrequent, indiscriminate updates on large-scale new data, or (2) frequent, sample-level updates. However, practical model deployment often operates in the gap between these two limit cases, as real-world applications often demand adaptation to specific subdomains, tasks or concepts -- spread over the entire, varying life c