Papers with RussianSuperGLUE

2 papers
Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian (2020.coling-main)

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Challenge: MRC in other languages, including Russian, has not been well-addressed due to the lack of high-quality and large-scale datasets.
Approach: They propose two Russian machine reading comprehension datasets that require reasoning over multiple sentences and commonsense knowledge to infer the answer.
Outcome: The proposed datasets are more complex than the original ones for Russian . the results show that the proposed models are challenging for advanced models .
Vygotsky Distance: Measure for Benchmark Task Similarity (2024.lrec-main)

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Challenge: GLUE, SuperGLUE and RussianSuperGLUE benchmarks are arbitrary sets of tasks that are not generalized.
Approach: They propose a theoretical instrument and an algorithm to calculate similarity between benchmark tasks . they use relative performance of the "students" on a given task to determine similarity .
Outcome: The proposed model reduces the number of evaluation tasks while maintaining high validation quality.

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