9 papers · 1 filter
Multimodal Evaluation of Russian-language Architectures
Artem Chervyakov, Ulyana Isaeva, Anton Emelyanov +15
Multimodal large language models (MLLMs) are currently at the center of research attention, showing rapid progress in scale and capabilities, yet their intelligence, limitations, a…
DRAGOn: Designing RAG On Periodically Updated Corpus
Fedor Chernogorskii, Sergei Averkiev, Liliya Kudraleeva +4
This paper introduces DRAGOn, method to design a RAG benchmark on a regularly updated corpus. It features recent reference datasets, a question generation framework, an automatic e…
MMTEB: Massive Multilingual Text Embedding Benchmark
Kenneth Enevoldsen, Isaac Chung, Imene Kerboua +83
Text embeddings are typically evaluated on a limited set of tasks, which are constrained by language, domain, and task diversity. To address these limitations and provide a more co…
Long Input Benchmark for Russian Analysis
Igor Churin, Murat Apishev, Maria Tikhonova +5
Recent advancements in Natural Language Processing (NLP) have fostered the development of Large Language Models (LLMs) that can solve an immense variety of tasks. One of the key as…
The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design
Artem Snegirev, Maria Tikhonova, Anna Maksimova +2
Embedding models play a crucial role in Natural Language Processing (NLP) by creating text embeddings used in various tasks such as information retrieval and assessing semantic tex…
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…