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The standard train/test split contains strong semantic clustering and substantial similarity between training and test images within the same MS COCO categories. This can inflate apparent reconstruction performance (see Shirakawa et al., 2025). For reconstruction studies it is advisable to create alternative splits where test stimuli contain categories not present during training, or where semantic and visual overlap between training and test images is minimized.