Imagen de Portada

Denoising Pre-Training and Customized Prompt Learning for Efficient Multi-Behavior Sequential Recommendation

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Hao, Han, Yongqiang, Wang, Kefan, Cheng, Kai, Wang, Zhen, Guo, Wei, Liu, Yong, Lian, Defu, Chen, Enhong
Formato:	Preprint
Publicado:	2024
Materias:	Information Retrieval Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation
por: Han, Yongqiang, et al.
Publicado: (2024)

Rethinking Purity and Diversity in Multi-Behavior Sequential Recommendation from the Frequency Perspective
por: Han, Yongqiang, et al.
Publicado: (2025)

Dataset Regeneration for Sequential Recommendation
por: Yin, Mingjia, et al.
Publicado: (2024)

Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation
por: Yin, Mingjia, et al.
Publicado: (2024)

DLF: Enhancing Explicit-Implicit Interaction via Dynamic Low-Order-Aware Fusion for CTR Prediction
por: Wang, Kefan, et al.
Publicado: (2025)

A Universal Framework for Compressing Embeddings in CTR Prediction
por: Wang, Kefan, et al.
Publicado: (2025)

A Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation
por: Zhang, Luankang, et al.
Publicado: (2024)

FuXi-Linear: Unleashing the Power of Linear Attention in Long-term Time-aware Sequential Recommendation
por: Ye, Yufei, et al.
Publicado: (2026)

Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction
por: Xu, Xiang, et al.
Publicado: (2024)

Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and Method
por: Liu, Ze, et al.
Publicado: (2024)

Generative Large Recommendation Models: Emerging Trends in LLMs for Recommendation
por: Wang, Hao, et al.
Publicado: (2025)

MDAP: A Multi-view Disentangled and Adaptive Preference Learning Framework for Cross-Domain Recommendation
por: Tong, Junxiong, et al.
Publicado: (2024)

FuXi-β: Towards a Lightweight and Fast Large-Scale Generative Recommendation Model
por: Ye, Yufei, et al.
Publicado: (2025)

Optimizing Sequential Recommendation Models with Scaling Laws and Approximate Entropy
por: Shen, Tingjia, et al.
Publicado: (2024)

Killing Two Birds with One Stone: Unifying Retrieval and Ranking with a Single Generative Recommendation Model
por: Zhang, Luankang, et al.
Publicado: (2025)

Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation
por: Shen, Tingjia, et al.
Publicado: (2024)

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

Scaling New Frontiers: Insights into Large Recommendation Models
por: Guo, Wei, et al.
Publicado: (2024)

Can Recommender Systems Teach Themselves? A Recursive Self-Improving Framework with Fidelity Control
por: Zhang, Luankang, et al.
Publicado: (2026)

FuXi-$α$: Scaling Recommendation Model with Feature Interaction Enhanced Transformer
por: Ye, Yufei, et al.
Publicado: (2025)

Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendation
por: Luo, Yucong, et al.
Publicado: (2024)

Efficient Personalized Reranking with Semi-Autoregressive Generation and Online Knowledge Distillation
por: Cheng, Kai, et al.
Publicado: (2026)

Dynamic Spectral Denoising with Global-Context Attention for Multi-Behavior Recommendation
por: Cai, Miaomiao, et al.
Publicado: (2026)

BBQRec: Behavior-Bind Quantization for Multi-Modal Sequential Recommendation
por: Li, Kaiyuan, et al.
Publicado: (2025)

Multi-Modal Multi-Behavior Sequential Recommendation with Conditional Diffusion-Based Feature Denoising
por: Cui, Xiaoxi, et al.
Publicado: (2025)

Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation
por: Liu, Chengkai, et al.
Publicado: (2024)

Preference Trajectory Modeling via Flow Matching for Sequential Recommendation
por: Li, Li, et al.
Publicado: (2025)

Quality-Aware Collaborative Multi-Positive Contrastive Learning for Sequential Recommendation
por: Wang, Wei
Publicado: (2026)

Empowering Denoising Sequential Recommendation with Large Language Model Embeddings
por: Wu, Tongzhou, et al.
Publicado: (2025)

From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models
por: Yin, Mingjia, et al.
Publicado: (2025)

SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
por: Zhang, Chi, et al.
Publicado: (2024)

Bridging User Dynamics: Transforming Sequential Recommendations with Schrödinger Bridge and Diffusion Models
por: Xie, Wenjia, et al.
Publicado: (2024)

BLADE: A Behavior-Level Data Augmentation Framework with Dual Fusion Modeling for Multi-Behavior Sequential Recommendation
por: Li, Yupeng, et al.
Publicado: (2025)

Towards Transfer-Efficient Multi-modal Sequential Recommendation with State Space Duality
por: Fan, Hao, et al.
Publicado: (2025)

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

Latent Factor Modeling with Expert Network for Multi-Behavior Recommendation
por: Yan, Mingshi, et al.
Publicado: (2026)

Generative Sequential Recommendation via Hierarchical Behavior Modeling
por: Wang, Zhefan, et al.
Publicado: (2025)

Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness
por: Cheng, Mingyue, et al.
Publicado: (2024)

Multi-Granularity Sequence Denoising with Weakly Supervised Signal for Sequential Recommendation
por: Li, Liang, et al.
Publicado: (2025)

Efficient Multi-task Prompt Tuning for Recommendation
por: Bai, Ting, et al.
Publicado: (2024)