papers

Publications (7)

cs.IR2024

UniSAR: Modeling User Transition Behaviors between Search and Recommendation

Teng Shi, Zihua Si, Jun Xu +6

Nowadays, many platforms provide users with both search and recommendation services as important tools for accessing information. The phenomenon has led to a correlation between us…

cs.IR2024

TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

Zihua Si, Lin Guan, ZhongXiang Sun +12

The significance of modeling long-term user interests for CTR prediction tasks in large-scale recommendation systems is progressively gaining attention among researchers and practi…

cs.SI2025

Pantheon: Personalized Multi-objective Ensemble Sort via Iterative Pareto Policy Optimization

Jiangxia Cao, Pengbo Xu, Yin Cheng +9

In this paper, we provide our milestone ensemble sort work and the first-hand practical experience, Pantheon, which transforms ensemble sorting from a "human-curated art" to a "mac…

cs.IR2023

TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou

Jianxin Chang, Chenbin Zhang, Zhiyi Fu +8

Life-long user behavior modeling, i.e., extracting a user's hidden interests from rich historical behaviors in months or even years, plays a central role in modern CTR prediction s…

cs.LG2026

PIT-SUN: A Deployable Empirical Marginal Transform Framework with Expectation-Consistent Recovery for Regression in Recommender Systems

Mingyu Zhao, Zhaohan Li, Zhenxiong Miao +4

Estimating original-space conditional expectations is central to value-driven recommender systems, including dwell time, GMV, and LTV forecasting. Standard MSE is expectation-consi…

cs.IR2023

KuaiSAR: A Unified Search And Recommendation Dataset

Zhongxiang Sun, Zihua Si, Xiaoxue Zang +5

The confluence of Search and Recommendation (S&R) services is vital to online services, including e-commerce and video platforms. The integration of S&R modeling is a highly intuit…

cs.IR2023

PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information

Jianxin Chang, Chenbin Zhang, Yiqun Hui +4

With the increase of content pages and interactive buttons in online services such as online-shopping and video-watching websites, industrial-scale recommender systems face challen…