Through the Looking Glass: Common Sense Consistency Evaluation of Weird
  Images
Authors: name: Elisei Rykov, name: Kseniia Petrushina, name: Kseniia Titova, name: Anton Razzhigaev, name: Alexander Panchenko, name: Vasily Konovalov

Measuring how real images look is a complex task in artificial intelligence
research. For example, an image of a boy with a vacuum cleaner in a desert
violates common sense. We introduce a novel method, which we call Through the
Looking Glass (TLG), to assess image common sense consistency using Large
Vision-Language Models (LVLMs) and Transformer-based encoder. By leveraging
LVLMs to extract atomic facts from these images, we obtain a mix of accurate
facts. We proceed by fine-tuning a compact attention-pooling classifier over
encoded atomic facts. Our TLG has achieved a new state-of-the-art performance
on the WHOOPS! and WEIRD datasets while leveraging a compact fine-tuning
component.