Papers by Kirill Tobola

1 papers
CoLeM: A framework for semantic interpretation of Russian-language tables based on contrastive learning (2025.acl-srw)

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Challenge: Existing methods for semantic interpretation of tables in Russian lack explicit semantics . tabular data are one of the key formats for presenting structured information in various domains ranging from scientific research to business analytics.
Approach: They propose a contrastive learning approach to minimize reliance on manual labeling and enhance the accuracy of column annotation for rare semantic types.
Outcome: The proposed method minimizes reliance on manual labeling and improves column annotation accuracy for rare semantic types.

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