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20202023
most citedRecent Advances in RecBole: Extensions with more Practical Considerations

6 citations · 12 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.IR20235 cited

User Behavior Simulation with Large Language Model based Agents

Lei Wang, Jingsen Zhang, Hao Yang +11

Simulating high quality user behavior data has always been a fundamental problem in human-centered applications, where the major difficulty originates from the intricate mechanism…

cs.IR20232 cited

REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation

Xu Chen, Jingsen Zhang, Lei Wang +6

Explainable recommendation has attracted much attention from the industry and academic communities. It has shown great potential for improving the recommendation persuasiveness, in…

cs.IR20226 cited

Recent Advances in RecBole: Extensions with more Practical Considerations

Lanling Xu, Zhen Tian, Gaowei Zhang +10

RecBole has recently attracted increasing attention from the research community. As the increase of the number of users, we have received a number of suggestions and update request…

cs.IR20221 cited

Recommendation with User Active Disclosing Willingness

Lei Wang, Xu Chen, Quanyu Dai +1

Recommender system has been deployed in a large amount of real-world applications, profoundly influencing people's daily life and production.Traditional recommender models mostly c…

cs.IR2020

RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

Wayne Xin Zhao, Shanlei Mu, Yupeng Hou +16

In recent years, there are a large number of recommendation algorithms proposed in the literature, from traditional collaborative filtering to deep learning algorithms. However, th…