Error Causal inference for Multi-Fusion models
In this paper, we propose an error causal inference method that could be used for finding dominant features for a faulty instance under a well-trained multi-modality input model, which could apply to any testing instance. We evaluate our method using a well-trained multi-modalities stylish caption generation model and find those causal inferences that could provide us the insights for next step optimization.
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