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2024年12月24日 · In this paper, we introduce MixMAS, a novel framework for sampling-based mixer architecture search tailored to multimodal learning. Our approach automatically selects the optimal MLP-based architecture for a given multimodal machine learning (MML) task.

In this paper, we present MixMAS, an automated framework for solving the problem of choosing which MLP-based archi-tecture to use for a given multimodal machine learning task (MML). Our contributions can be summarized as follows: 1) We propose an automated pipeline for selecting the optimal MLP-based architecture for multimodal tasks.

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2024年12月24日 · In this paper, we introduce MixMAS, a novel framework for sampling-based mixer architecture search tailored to multimodal learning. Our approach automatically selects the optimal MLP-based architecture for a given multimodal machine learning (MML) task.