65 citations · 292 across the 21 of their papers we have counts for
4 papers · 1 filter
Best Prompts for Text-to-Image Models and How to Find Them
Nikita Pavlichenko, Dmitry Ustalov
Recent progress in generative models, especially in text-guided diffusion models, has enabled the production of aesthetically-pleasing imagery resembling the works of professional…
Clustering Without Knowing How To: Application and Evaluation
Daniil Likhobaba, Daniil Fedulov, Dmitry Ustalov
Crowdsourcing allows running simple human intelligence tasks on a large crowd of workers, enabling solving problems for which it is difficult to formulate an algorithm or train a m…
IMDB-WIKI-SbS: An Evaluation Dataset for Crowdsourced Pairwise Comparisons
Nikita Pavlichenko, Dmitry Ustalov
Today, comprehensive evaluation of large-scale machine learning models is possible thanks to the open datasets produced using crowdsourcing, such as SQuAD, MS COCO, ImageNet, Super…
Learning from Crowds with Crowd-Kit
Dmitry Ustalov, Nikita Pavlichenko, Boris Tseitlin
This paper presents Crowd-Kit, a general-purpose computational quality control toolkit for crowdsourcing. Crowd-Kit provides efficient and convenient implementations of popular qua…