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It's been a long time since I've read it, but I vaguely remember a write-up many years ago (before we used ML for NSFW detection) about how either yellow images would often produce false positives in popular detection algos, and/or about how the yellow-ness of an image could be used as a lower-tech proxy for basic NSFW detection (seemingly because of its proximity to some common skin tones).

I don't know if either of these are relevant here, but it's possible a weight on Yellow Images could be related to NSFW images.



Upon closer inspection, they have a lot of weights regarding "yellowness" [0], and several of them say "based on Toloka", which is an antifraud service that assigns colors to violation levels [1].

So my suspicion above is probably wrong, and "yellow" images probably refer to a Toloka score/color for whatever domain the images are hosted on.

[0] https://yandex-explorer.herokuapp.com/search?q=yellow&o=all

[1] https://join.toloka.ai/blog/project-limits/


Wrong Toloka. Yandex has its own Toloka which is a crowdsourcing platform for repetitive tasks that inherently require a human in the loop. In other words, this factor comes from real human assessors hired via Toloka.




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