6 papers
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…
MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks
Artem Chervyakov, Alexander Kharitonov, Pavel Zadorozhny +20
Advancements in LLMs have enhanced task automation in software engineering; however, current evaluations primarily focus on natural language tasks, overlooking code quality. Most b…
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…
Eye of Judgement: Dissecting the Evaluation of Russian-speaking LLMs with POLLUX
Nikita Martynov, Anastasia Mordasheva, Dmitriy Gorbetskiy +8
We introduce POLLUX, a comprehensive open-source benchmark designed to evaluate the generative capabilities of large language models (LLMs) in Russian. Our main contribution is a n…
REPA: Russian Error Types Annotation for Evaluating Text Generation and Judgment Capabilities
Alexander Pugachev, Alena Fenogenova, Vladislav Mikhailov +1
Recent advances in large language models (LLMs) have introduced the novel paradigm of using LLMs as judges, where an LLM evaluates and scores the outputs of another LLM, which ofte…
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…