Qinglin Jia

According to our database, Qinglin Jia authored at least 27 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

DIET: Learning to Distill Dataset Continually for Recommender Systems.

Jiaqing Zhang, Hao Wang, Mingjia Yin, Bo Chen, Qinglin Jia, Rui Zhou, Ruiming Tang, ChaoYi Ma, Enhong Chen

CoRR, March, 2026

SMES: Towards Scalable Multi-Task Recommendation via Expert Sparsity.

Yukun Zhang, Si Dong, Xu Wang, Bo Chen, Qinglin Jia, Shengzhe Wang, Jinlong Jiao, Runhan Li, Jiaqing Liu, Chaoyi Ma, Ruiming Tang, Guorui Zhou, Han Li, Kun Gai

CoRR, February, 2026

ArmNet: Robust Arm Motion Tracking for IoT Interaction Using a Single IMU.

Ke Wang, Qinglin Jia, Xin Xie, Xiulong Liu, Xiaoyi Tao, Sheng Chen, Keqiu Li

IEEE Internet Things J., 2026

FairFS: Addressing Deep Feature Selection Biases for Recommender System.

Xianquan Wang, Zhaocheng Du, Jieming Zhu, Qinglin Jia, Zhenhua Dong, Kai Zhang

Proceedings of the ACM Web Conference 2026, 2026

REACTION: Parameter-Efficient Learning for Recommendation.

Song-Li Wu, Zhaocheng Du, Qinglin Jia, Zhenhua Dong

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

No One Left Behind: How to Exploit the Incomplete and Skewed Multi-Label Data for Conversion Rate Prediction.

Qinglin Jia, Zhaocheng Du, Chuhan Wu, Huifeng Guo, Ruiming Tang, Shuting Shi, Muyu Zhang

CoRR, December, 2025

CHOP: Mobile Operating Assistant with Constrained High-frequency Optimized Subtask Planning.

Yuqi Zhou, Shuai Wang, Sunhao Dai, Qinglin Jia, Zhaocheng Du, Zhenhua Dong, Jun Xu

CoRR, March, 2025

MIT: A Multi-Tower Information Transfer Framework Based on Hierarchical Task Relationship Modeling.

Rui Zhou, Hao Wang, Wei Guo, Qinglin Jia, Wenjia Xie, Xiang Xu, Yong Liu, Defu Lian, Enhong Chen

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Few-shot LLM Synthetic Data with Distribution Matching.

Jiyuan Ren, Zhaocheng Du, Zhihao Wen, Qinglin Jia, Sunhao Dai, Chuhan Wu, Zhenhua Dong

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents.

Yuqi Zhou, Sunhao Dai, Shuai Wang, Kaiwen Zhou, Qinglin Jia, Jun Xu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

TayFCS: Towards Light Feature Combination Selection for Deep Recommender Systems.

Xianquan Wang, Zhaocheng Du, Jieming Zhu, Chuhan Wu, Qinglin Jia, Zhenhua Dong

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2024

RecSys Arena: Pair-wise Recommender System Evaluation with Large Language Models.

Zhuo Wu, Qinglin Jia, Chuhan Wu, Zhaocheng Du, Shuai Wang, Zan Wang, Zhenhua Dong

CoRR, 2024

Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation.

Yuang Zhao, Zhaocheng Du, Qinglin Jia, Linxuan Zhang, Zhenhua Dong, Ruiming Tang

CoRR, 2024

LightCS: Selecting Quadratic Feature Crosses in Linear Complexity.

Zhaocheng Du, Junhao Chen, Qinglin Jia, Chuhan Wu, Jieming Zhu, Zhenhua Dong, Ruiming Tang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Ranking-Aware Unbiased Post-Click Conversion Rate Estimation via AUC Optimization on Entire Exposure Space.

Yu Liu, Qinglin Jia, Shuting Shi, Chuhan Wu, Zhaocheng Du, Zheng Xie, Ruiming Tang, Muyu Zhang, Ming Li

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

A Tutorial on Feature Interpretation in Recommender Systems.

Zhaocheng Du, Chuhan Wu, Qinglin Jia, Jieming Zhu, Xu Chen

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Confidence-Aware Multi-Field Model Calibration.

Yuang Zhao, Chuhan Wu, Qinglin Jia, Hong Zhu, Jia Yan, Libin Zong, Linxuan Zhang, Zhenhua Dong, Muyu Zhang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Contrastive Multi-view Framework for Customer Lifetime Value Prediction.

Chuhan Wu, Jingjie Li, Qinglin Jia, Hong Zhu, Yuan Fang, Ruiming Tang

CoRR, 2023

Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation.

Xiaofan Liu, Qinglin Jia, Chuhan Wu, Jingjie Li, Quanyu Dai, Lin Bo, Rui Zhang, Ruiming Tang

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

FINAL: Factorized Interaction Layer for CTR Prediction.

Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Customer Lifetime Value Prediction: Towards the Paradigm Shift of Recommender System Objectives.

Chuhan Wu, Qinglin Jia, Zhenhua Dong, Ruiming Tang

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction.

Yifan Wang, Peijie Sun, Min Zhang, Qinglin Jia, Jingjie Li, Shaoping Ma

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Optimal Design of Multimodal Traffic Strategies in Emergency Evacuation Considering Background Traffic.

Yang Yang, Tao Zhang, Qinglin Jia, Gang Cheng, Qian Yu, Minjie Jin

IEEE Access, 2022

2021

AMM: Attentive Multi-field Matching for News Recommendation.

Qi Zhang, Qinglin Jia, Chuyuan Wang, Jingjie Li, Zhaowei Wang, Xiuqiang He

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

RMBERT: News Recommendation via Recurrent Reasoning Memory Network over BERT.

Qinglin Jia, Jingjie Li, Qi Zhang, Xiuqiang He, Jieming Zhu

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

UNBERT: User-News Matching BERT for News Recommendation.

Qi Zhang, Jingjie Li, Qinglin Jia, Chuyuan Wang, Jieming Zhu, Zhaowei Wang, Xiuqiang He

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2019

Learning Continuous User and Item Representations for Neural Collaborative Filtering.

Qinglin Jia, Xiao Su, Zhonghai Wu

Proceedings of the Knowledge Science, Engineering and Management, 2019