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cs.AI2026
UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks
Zhilun Zhou, Jianghao Yu, Yuming Lin +4
Large language model (LLM) agents have been widely applied in automating data science tasks. However, existing methods typically rely on a limited set of provided datasets, and the…
cs.IR2026
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…