Papers by Pavel Posokhov

1 papers
Relevance Scores Calibration for Ranked List Truncation via TMP Adapter (2025.findings-acl)

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Challenge: ranked list truncation methods struggle with limited capacity, unstable training and inconsistency of selected thresholds.
Approach: They propose a new approach that incorporates the Threshold Margin Penalty as an additive loss function to calibrate ranking model relevance scores for ranked list truncation.
Outcome: The proposed method improves on retrieval datasets and offers theoretical and practical benefits.

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