What question did this study set out to answer?

This paper aims to present the algorithms implemented by the UTIRL team for the NTCIR-16 ULTRE Task.

April 1, 2026Open Access

UTIRL at the NTCIR-16 ULTRE Task

Key Points

This paper aims to present the algorithms implemented by the UTIRL team for the NTCIR-16 ULTRE Task.
Participated in both Offline and Online unbiased learning-to-rank subtasks.
Implemented a newly proposed ULTR algorithm in the Offline subtask.
Used an ensemble of ten models from five different algorithms on two neural networks.
Applied three algorithms trained on a deep neural network in the Online subtask.
Analyzed the official results from both tasks to evaluate algorithm performance.

Abstract

The UTIRL team participated in both Offline and Online unbiased learning-to-rank (ULTR) (Chinese) subtasks of the NTCIR-16 ULTRE Task. This paper describes our implemented algorithms and analysis the official results. In the Offline ULTR subtask, we tried a newly proposed ULTR algorithm and an ensemble of ten models consisting of five different algorithms on two neural networks. In the Online ULTR subtask, we used three algorithms trained on a deep neural network.

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