Cong Xu

According to our database, Cong Xu authored at least 20 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation.

Minhao Wang, Yunhang He, Cong Xu, Zhangchi Zhu, Wei Zhang

CoRR, August, 2025

Pattern-Wise Transparent Sequential Recommendation.

Kun Ma, Cong Xu, Zeyuan Chen, Wei Zhang

IEEE Trans. Knowl. Data Eng., June, 2025

Pushing the Limits of Low-Bit Optimizers: A Focus on EMA Dynamics.

Cong Xu, Wenbin Liang, Mo Yu, Anan Liu, Ke-Yue Zhang, Lizhuang Ma, Jianyong Wang, Jun Wang, Wei Zhang

CoRR, May, 2025

Understanding Adversarial Robustness From Feature Maps of Convolutional Layers.

Cong Xu, Wei Zhang, Jun Wang, Min Yang

IEEE Trans. Neural Networks Learn. Syst., March, 2025

Collaborative Filtering Meets Spectrum Shift: Connecting User-Item Interaction with Graph-Structured Side Information.

Yunhang He, Cong Xu, Jun Wang, Wei Zhang

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

STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation.

Cong Xu, Yunhang He, Jun Wang, Wei Zhang

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

StableGCN: Decoupling and Reconciling Information Propagation for Collaborative Filtering.

Cong Xu, Jun Wang, Wei Zhang

IEEE Trans. Knowl. Data Eng., June, 2024

CAdam: Confidence-Based Optimization for Online Learning.

Shaowen Wang, Anan Liu, Jian Xiao, Huan Liu, Yuekui Yang, Cong Xu, Qianqian Pu, Suncong Zheng, Wei Zhang, Jian Li

CoRR, 2024

Are LLM-based Recommenders Already the Best? Simple Scaled Cross-entropy Unleashes the Potential of Traditional Sequential Recommenders.

Cong Xu, Zhangchi Zhu, Mo Yu, Jun Wang, Jianyong Wang, Wei Zhang

CoRR, 2024

Understanding the Role of Cross-Entropy Loss in Fairly Evaluating Large Language Model-based Recommendation.

Cong Xu, Zhangchi Zhu, Jun Wang, Jianyong Wang, Wei Zhang

CoRR, 2024

Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution.

Cong Xu, Jun Wang, Jianyong Wang, Wei Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2022

Adversarial momentum-contrastive pre-training.

Cong Xu, Dan Li, Min Yang

Pattern Recognit. Lett., 2022

An orthogonal classifier for improving the adversarial robustness of neural networks.

Cong Xu, Xiang Li, Min Yang

Inf. Sci., 2022

Less Emphasis on Difficult Layer Regions: Curriculum Learning for Singularly Perturbed Convection-Diffusion-Reaction Problems.

Yufeng Wang, Cong Xu, Min Yang, Jin Zhang

CoRR, 2022

Understanding Adversarial Robustness from Feature Maps of Convolutional Layers.

Cong Xu, Min Yang

CoRR, 2022

Improve Deep Image Inpainting by Emphasizing the Complexity of Missing Regions.

Yufeng Wang, Dan Li, Cong Xu, Min Yang

CoRR, 2022

2021

Missingness Augmentation: A General Approach for Improving Generative Imputation Models.

Yufeng Wang, Dan Li, Cong Xu, Min Yang

CoRR, 2021

2020

Adversarial Momentum-Contrastive Pre-Training.

Cong Xu, Min Yang

CoRR, 2020

Improve Adversarial Robustness via Weight Penalization on Classification Layer.

Cong Xu, Dan Li, Min Yang

CoRR, 2020

2019

A Fast deflation Method for Sparse Principal Component Analysis via Subspace Projections.

Cong Xu, Min Yang, Jin Zhang

CoRR, 2019