46 citations · 50 across the 6 of their papers we have counts for
6 papers
Dually Enhanced Propensity Score Estimation in Sequential Recommendation
Chen Xu, Jun Xu, Xu Chen +2
Sequential recommender systems train their models based on a large amount of implicit user feedback data and may be subject to biases when users are systematically under/over-expos…
Multi-Modal Experience Inspired AI Creation
Qian Cao, Xu Chen, Ruihua Song +3
AI creation, such as poem or lyrics generation, has attracted increasing attention from both industry and academic communities, with many promising models proposed in the past few…
Debiased Recommendation with Neural Stratification
Quanyu Dai, Zhenhua Dong, Xu Chen
Debiased recommender models have recently attracted increasing attention from the academic and industry communities. Existing models are mostly based on the technique of inverse pr…
Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction
Weijie Yu, Zhongxiang Sun, Jun Xu +4
As an essential operation of legal retrieval, legal case matching plays a central role in intelligent legal systems. This task has a high demand on the explainability of matching r…
RecBole 2.0: Towards a More Up-to-Date Recommendation Library
Wayne Xin Zhao, Yupeng Hou, Xingyu Pan +16
In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics a…
Learning to Identify Top Elo Ratings: A Dueling Bandits Approach
Xue Yan, Yali Du, Binxin Ru +3
The Elo rating system is widely adopted to evaluate the skills of (chess) game and sports players. Recently it has been also integrated into machine learning algorithms in evaluati…