3 papers
cs.CL2025
Gamayun's Path to Multilingual Mastery: Cost-Efficient Training of a 1.5B-Parameter LLM
Alexander Podolskiy, Semen Molokov, Timofey Gerasin +14
We present Gamayun, a 1.5B-parameter multilingual language model trained entirely from scratch on 2.5T tokens. Designed for efficiency and deployment in resource-constrained enviro…
cs.LG2025
Commute Your Domains: Trajectory Optimality Criterion for Multi-Domain Learning
Alexey Rukhovich, Alexander Podolskiy, Irina Piontkovskaya
In multi-domain learning, a single model is trained on diverse data domains to leverage shared knowledge and improve generalization. The order in which the data from these domains…
cs.CL2023
Efficient Grammatical Error Correction Via Multi-Task Training and Optimized Training Schedule
Andrey Bout, Alexander Podolskiy, Sergey Nikolenko +1
Progress in neural grammatical error correction (GEC) is hindered by the lack of annotated training data. Sufficient amounts of high-quality manually annotated data are not availab…