13 citations · 15 across the 5 of their papers we have counts for
5 papers
Disentangled Interest Network for Out-of-Distribution CTR Prediction
Yu Zheng, Chen Gao, Jianxin Chang +5
Click-through rate (CTR) prediction, which estimates the probability of a user clicking on a given item, is a critical task for online information services. Existing approaches oft…
Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method
Chen Yang, Sunhao Dai, Yupeng Hou +4
Reciprocal recommender systems~(RRS), conducting bilateral recommendations between two involved parties, have gained increasing attention for enhancing matching efficiency. However…
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems
Kai Zheng, Haijun Zhao, Rui Huang +6
The Probability Ranking Principle (PRP) has been considered as the foundational standard in the design of information retrieval (IR) systems. The principle requires an IR module's…
The 2nd Workshop on Recommendation with Generative Models
Wenjie Wang, Yang Zhang, Xinyu Lin +7
The rise of generative models has driven significant advancements in recommender systems, leaving unique opportunities for enhancing users' personalized recommendations. This works…
KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph
Jinhao Jiang, Kun Zhou, Wayne Xin Zhao +4
In this paper, we aim to improve the reasoning ability of large language models (LLMs) over knowledge graphs (KGs) to answer complex questions. Inspired by existing methods that de…