Through the Looking Glass: Common Sense Consistency Evaluation of Weird
  Images
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.
682cc6b48b0dfc6de9ed8de0
Elisei Rykov
claimed_verified
2025-05-20T18:25:43.631Z
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Rykov Elisei
user
lmeribal
682cc6b48b0dfc6de9ed8de1
Kseniia Petrushina
claimed_verified
2025-05-20T19:28:55.437Z
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Kseniia
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rrevoid
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Kseniia Titova
claimed_verified
2025-06-24T09:33:10.970Z
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Kseniia
user
sitnich
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Anton Razzhigaev
claimed_verified
2025-09-01T07:56:02.806Z
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Anton Razzhigaev
user
razzant
682cc6b48b0dfc6de9ed8de4
Alexander Panchenko
claimed_verified
2025-08-19T11:22:04.657Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/1662046050710-605473729d7c1d4d81b7e52b.jpeg
Alexander Panchenko
user
apanc
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Vasily Konovalov
claimed_verified
2025-05-20T19:28:57.499Z
622b1f6b9f6139daa8e998ce
/avatars/842719c100a5969be75d04da97333675.svg
Vasily Konovalov
user
Vasily
Through the Looking Glass: Common Sense Consistency Evaluation of Weird
  Images
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.
A new method, Through the Looking Glass (TLG), uses Large Vision-Language Models and Transformer-based encoders to improve image common sense consistency assessment on the WHOOPS! and WEIRD datasets.
Large Vision-Language Models (LVLMs) Transformer-based encoder attention-pooling classifier WHOOPS! WEIRD datasets