Instruction: Explain strategies for dealing with instances where one or more modalities are missing in a dataset.
Context: This question evaluates the candidate's ability to handle incomplete multimodal data, a common issue in real-world datasets, ensuring robust model performance even with incomplete information.
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The way I'd approach it in an interview is this: I assume missing modalities will happen in production and design for graceful degradation from the start. That can mean modality-dropout training, fallback pathways, uncertainty-aware fusion, and models that can...