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Sequential Compositional Generalization in Multimodal Models
April 19, 2024, 4:47 a.m. | Semih Yagcioglu, Osman Batur \.Ince, Aykut Erdem, Erkut Erdem, Desmond Elliott, Deniz Yuret
cs.CL updates on arXiv.org arxiv.org
Abstract: The rise of large-scale multimodal models has paved the pathway for groundbreaking advances in generative modeling and reasoning, unlocking transformative applications in a variety of complex tasks. However, a pressing question that remains is their genuine capability for stronger forms of generalization, which has been largely underexplored in the multimodal setting. Our study aims to address this by examining sequential compositional generalization using \textsc{CompAct} (\underline{Comp}ositional \underline{Act}ivities)\footnote{Project Page: \url{http://cyberiada.github.io/CompAct}}, a carefully constructed, perceptually grounded dataset set …
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