Diagnosing Vision Language Models’ Perception by Leveraging Human Methods for Color Vision Deficiencies (2026.eacl-long)
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| Challenge: | Large-scale Vision-Language Models (LVLMs) are being deployed in real-world settings that require visual inference. |
| Approach: | They evaluate LVLMs' ability to account for variation in color perception using the Ishihara Test. |
| Outcome: | The proposed models fail to reproduce the perceptual outcomes experienced by affected individuals and default to normative color perception. |
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