65 citations · 73 across the 7 of their papers we have counts for
7 papers
Mellum2 Technical Report
Marko Kojic, Ivan Bondyrev, Aral de Moor +6
We present Mellum 2, an open-weight 12B-parameter Mixture-of-Experts (MoE) language model with 2.5B active parameters per token. Mellum 2 is a general-purpose language model specia…
Mellum: Production-Grade in-IDE Contextual Code Completion with Multi-File Project Understanding
Nikita Pavlichenko, Iurii Nazarov, Ivan Dolgov +10
We present the Mellum models family, open-weight code completion models designed for interactive use in JetBrains IDEs. Mellums have 4B parameters, adopt a Llama-style architecture…
Toloka Visual Question Answering Benchmark
Dmitry Ustalov, Nikita Pavlichenko, Sergey Koshelev +2
In this paper, we present Toloka Visual Question Answering, a new crowdsourced dataset allowing comparing performance of machine learning systems against human level of expertise i…
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…
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…
CrowdSpeech and VoxDIY: Benchmark Datasets for Crowdsourced Audio Transcription
Nikita Pavlichenko, Ivan Stelmakh, Dmitry Ustalov
Domain-specific data is the crux of the successful transfer of machine learning systems from benchmarks to real life. In simple problems such as image classification, crowdsourcing…