1.6k citations · 1.7k across the 8 of their papers we have counts for
8 papers
A Survey on Large Language Model based Autonomous Agents
Lei Wang, Chen Ma, Xueyang Feng +10
Autonomous agents have long been a prominent research focus in both academic and industry communities. Previous research in this field often focuses on training agents with limited…
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…
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…
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…
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…
Sequential Recommendation with Causal Behavior Discovery
Zhenlei Wang, Xu Chen, Rui Zhou +3
The key of sequential recommendation lies in the accurate item correlation modeling. Previous models infer such information based on item co-occurrences, which may fail to capture…
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…
Learning to Match Jobs with Resumes from Sparse Interaction Data using Multi-View Co-Teaching Network
Shuqing Bian, Xu Chen, Wayne Xin Zhao +5
With the ever-increasing growth of online recruitment data, job-resume matching has become an important task to automatically match jobs with suitable resumes. This task is typical…