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Towards Disentangling Relevance and Bias in Unbiased Learning to Rank

Towards Disentangling Relevance and Bias in Unbiased Learning to Rank

28 December 2022
Yunan Zhang
Le Yan
Zhen Qin
Honglei Zhuang
Jiaming Shen
Xuanhui Wang
Michael Bendersky
Marc Najork
    CML
ArXivPDFHTML

Papers citing "Towards Disentangling Relevance and Bias in Unbiased Learning to Rank"

4 / 4 papers shown
Title
Unbiased Learning to Rank with Query-Level Click Propensity Estimation: Beyond Pointwise Observation and Relevance
Unbiased Learning to Rank with Query-Level Click Propensity Estimation: Beyond Pointwise Observation and Relevance
Lulu Yu
Keping Bi
J. Guo
Shihao Liu
Dawei Yin
Xueqi Cheng
68
0
0
17 Feb 2025
Identifiability Matters: Revealing the Hidden Recoverable Condition in
  Unbiased Learning to Rank
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
Mouxiang Chen
Chenghao Liu
Zemin Liu
Zhuo Li
Jianling Sun
CML
34
2
0
27 Sep 2023
A General Framework for Debiasing in CTR Prediction
A General Framework for Debiasing in CTR Prediction
Wenjie Chu
Shen Li
Chao Chen
Longfei Xu
Hengbin Cui
Kaikui Liu
CML
42
4
0
06 Dec 2021
Improving Deep Learning For Airbnb Search
Improving Deep Learning For Airbnb Search
Malay Haldar
Mustafa Abdool
Prashant Ramanathan
Tyler Sax
Lanbo Zhang
Aamir Mansawala
Shulin Yang
B. Turnbull
Junshuo Liao
41
39
0
10 Feb 2020
1