  Minimal pairs are a well-established approach to evaluating the grammatical
knowledge of language models. However, existing resources for minimal pairs
address a limited number of languages and lack diversity of language-specific
grammatical phenomena. This paper introduces the Russian Benchmark of
Linguistic Minimal Pairs (RuBLiMP), which includes 45k pairs of sentences that
differ in grammaticality and isolate a morphological, syntactic, or semantic
phenomenon. In contrast to existing benchmarks of linguistic minimal pairs,
RuBLiMP is created by applying linguistic perturbations to automatically
annotated sentences from open text corpora and carefully curating test data. We
describe the data collection protocol and present the results of evaluating 25
language models in various scenarios. We find that the widely used language
models for Russian are sensitive to morphological and agreement-oriented
contrasts but fall behind humans on phenomena requiring understanding of
structural relations, negation, transitivity, and tense. RuBLiMP, the codebase,
and other materials are publicly available.
