Cover Image

Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tan, Juntao, Heinecke, Shelby, Liu, Zhiwei, Chen, Yongjun, Zhang, Yongfeng, Wang, Huan
Format:	Preprint
Published:	2023
Subjects:	Information Retrieval Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Personalized Multi-task Training for Recommender System
by: Yang, Liangwei, et al.
Published: (2024)

Sequential Recommendation with Controllable Diversification: Representation Degeneration and Diversity
by: Fan, Ziwei, et al.
Published: (2023)

Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems
by: Cao, Yuwei, et al.
Published: (2024)

SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
by: Xu, Wujiang, et al.
Published: (2024)

End-to-End Graph-Sequential Representation Learning for Accurate Recommendations
by: Baikalov, Vladimir, et al.
Published: (2024)

Position-Aware Sequential Attention for Accurate Next Item Recommendations
by: Nabiev, Timur, et al.
Published: (2026)

Pre-trained Language Model and Knowledge Distillation for Lightweight Sequential Recommendation
by: Li, Li, et al.
Published: (2024)

A Survey on Trustworthy Recommender Systems
by: Ge, Yingqiang, et al.
Published: (2022)

Facet-Aware Multi-Head Mixture-of-Experts Model for Sequential Recommendation
by: Liu, Mingrui, et al.
Published: (2024)

Retrieve-then-Adapt: Retrieval-Augmented Test-Time Adaptation for Sequential Recommendation
by: Tang, Xing, et al.
Published: (2026)

Sequential Recommendation via Adaptive Robust Attention with Multi-dimensional Embeddings
by: Pang, Linsey, et al.
Published: (2024)

Robust Reinforcement Learning Objectives for Sequential Recommender Systems
by: Mozifian, Melissa, et al.
Published: (2023)

A Systematic Survey on Federated Sequential Recommendation
by: Li, Yichen, et al.
Published: (2025)

Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach
by: Xu, Wujiang, et al.
Published: (2023)

Towards Robust Recommendation: A Review and an Adversarial Robustness Evaluation Library
by: Cheng, Lei, et al.
Published: (2024)

AsarRec: Adaptive Sequential Augmentation for Robust Self-supervised Sequential Recommendation
by: Zhang, Kaike, et al.
Published: (2025)

Making Recommender Systems More Knowledgeable: A Framework to Incorporate Side Information
by: Jiang, Yukun, et al.
Published: (2024)

Producer-Fairness in Sequential Bundle Recommendation
by: Rio, Alexandre, et al.
Published: (2025)

Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems
by: Kolodner, Matthew, et al.
Published: (2024)

Oracle-guided Dynamic User Preference Modeling for Sequential Recommendation
by: Xia, Jiafeng, et al.
Published: (2024)

Improving the Shortest Plank: Vulnerability-Aware Adversarial Training for Robust Recommender System
by: Zhang, Kaike, et al.
Published: (2024)

OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems
by: Xu, Shuyuan, et al.
Published: (2023)

CAST: Modeling Semantic-Level Transitions for Complementary-Aware Sequential Recommendation
by: Zhang, Qian, et al.
Published: (2026)

CSRec: Rethinking Sequential Recommendation from A Causal Perspective
by: Liu, Xiaoyu, et al.
Published: (2024)

Efficient and Robust Regularized Federated Recommendation
by: Liu, Langming, et al.
Published: (2024)

Knowledge Graph Context-Enhanced Diversified Recommendation
by: Liu, Xiaolong, et al.
Published: (2023)

Scaling Generative Recommendations with Context Parallelism on Hierarchical Sequential Transducers
by: Dong, Yue, et al.
Published: (2025)

Personalized Ranking on Cascading Behavior Graphs for Accurate Multi-Behavior Recommendation
by: Ko, Geonwoo, et al.
Published: (2025)

Measuring Recency Bias In Sequential Recommendation Systems
by: Oh, Jeonglyul, et al.
Published: (2024)

Dual Adversarial Perturbators Generate rich Views for Recommendation
by: Zhang, Lijun, et al.
Published: (2024)

TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation
by: Zhang, Jiaqing, et al.
Published: (2025)

Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
by: Zhang, Hao, et al.
Published: (2023)

An Efficient Continuous Control Perspective for Reinforcement-Learning-based Sequential Recommendation
by: Wang, Jun, et al.
Published: (2024)

Cloud-Device Collaborative Agents for Sequential Recommendation
by: Long, Jing, et al.
Published: (2025)

When and What to Recommend: Joint Modeling of Timing and Content for Active Sequential Recommendation
by: Chai, Jin, et al.
Published: (2025)

Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach
by: Chen, Jialei, et al.
Published: (2025)

Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
by: Escobedo, Gustavo, et al.
Published: (2024)

AlignRec: Aligning and Training in Multimodal Recommendations
by: Liu, Yifan, et al.
Published: (2024)

Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks
by: Su, Jinyan, et al.
Published: (2024)

From Agnostic to Specific: Latent Preference Diffusion for Multi-Behavior Sequential Recommendation
by: Yang, Ruochen, et al.
Published: (2026)