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NeuCME: Toward Dynamic Multimodal Continual Learning via Neural Combinatorics of Multiple Experts
Multimodal continual learning has recently shown great potential for developing agents with human-like intelligence by continuously learning new tasks across multiple modalities. However, existing methods typically assume that the set of modalities per task is predefined and fixed. In this paper, we
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