584 citations · 3.1k across the 56 of their papers we have counts for
14 papers · 1 filter
Whole Page Unbiased Learning to Rank
Haitao Mao, Lixin Zou, Yujia Zheng +5
The page presentation biases in the information retrieval system, especially on the click behavior, is a well-known challenge that hinders improving ranking models' performance wit…
Approximated Doubly Robust Search Relevance Estimation
Lixin Zou, Changying Hao, Hengyi Cai +6
Extracting query-document relevance from the sparse, biased clickthrough log is among the most fundamental tasks in the web search system. Prior art mainly learns a relevance judgm…
Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation
Boming Zhao, Bangbang Yang, Zhenyang Li +6
Expanding an existing tourist photo from a partially captured scene to a full scene is one of the desired experiences for photography applications. Although photo extrapolation has…
Model-based Unbiased Learning to Rank
Dan Luo, Lixin Zou, Qingyao Ai +3
Unbiased Learning to Rank (ULTR) that learns to rank documents with biased user feedback data is a well-known challenge in information retrieval. Existing methods in unbiased learn…
A Large Scale Search Dataset for Unbiased Learning to Rank
Lixin Zou, Haitao Mao, Xiaokai Chu +4
The unbiased learning to rank (ULTR) problem has been greatly advanced by recent deep learning techniques and well-designed debias algorithms. However, promising results on the exi…
Geometry Contrastive Learning on Heterogeneous Graphs
Shichao Zhu, Chuan Zhou, Anfeng Cheng +4
Self-supervised learning (especially contrastive learning) methods on heterogeneous graphs can effectively get rid of the dependence on supervisory data. Meanwhile, most existing r…