5 citations · 7 across the 4 of their papers we have counts for
4 papers
GigaEmbeddings: Efficient Russian Language Embedding Model
Egor Kolodin, Daria Khomich, Nikita Savushkin +2
We introduce GigaEmbeddings, a novel framework for training high-performance Russian-focused text embeddings through hierarchical instruction tuning of the decoder-only LLM designe…
GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture
GigaChat team, Mamedov Valentin, Evgenii Kosarev +31
Generative large language models (LLMs) have become crucial for modern NLP research and applications across various languages. However, the development of foundational models speci…
MERA: A Comprehensive LLM Evaluation in Russian
Alena Fenogenova, Artem Chervyakov, Nikita Martynov +16
Over the past few years, one of the most notable advancements in AI research has been in foundation models (FMs), headlined by the rise of language models (LMs). As the models' siz…
Large Raw Emotional Dataset with Aggregation Mechanism
Vladimir Kondratenko, Artem Sokolov, Nikolay Karpov +3
We present a new data set for speech emotion recognition (SER) tasks called Dusha. The corpus contains approximately 350 hours of data, more than 300 000 audio recordings with Russ…