A Comprehensive Survey on Retrieval Methods in Recommender Systems
Fuente:
arXiv
Guardado en:
| Autores principales: | Huang, Junjie, Chen, Jizheng, Lin, Jianghao, Qin, Jiarui, Feng, Ziming, Zhang, Weinan, Yu, Yong |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Unleashing the Potential of Multi-Channel Fusion in Retrieval for Personalized Recommendations
por: Huang, Junjie, et al.
Publicado: (2024)
por: Huang, Junjie, et al.
Publicado: (2024)
Beyond Graph Convolution: Multimodal Recommendation with Topology-aware MLPs
por: Huang, Junjie, et al.
Publicado: (2024)
por: Huang, Junjie, et al.
Publicado: (2024)
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation
por: Chen, Jizheng, et al.
Publicado: (2024)
por: Chen, Jizheng, et al.
Publicado: (2024)
D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems
por: Qin, Jiarui, et al.
Publicado: (2024)
por: Qin, Jiarui, et al.
Publicado: (2024)
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation
por: Zhu, Jiachen, et al.
Publicado: (2024)
por: Zhu, Jiachen, et al.
Publicado: (2024)
Learning ID-free Item Representation with Token Crossing for Multimodal Recommendation
por: Zhang, Kangning, et al.
Publicado: (2024)
por: Zhang, Kangning, et al.
Publicado: (2024)
A Survey on Diffusion Models for Recommender Systems
por: Lin, Jianghao, et al.
Publicado: (2024)
por: Lin, Jianghao, et al.
Publicado: (2024)
Why Not Together? A Multiple-Round Recommender System for Queries and Items
por: Jin, Jiarui, et al.
Publicado: (2024)
por: Jin, Jiarui, et al.
Publicado: (2024)
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
por: Lin, Jianghao, et al.
Publicado: (2023)
por: Lin, Jianghao, et al.
Publicado: (2023)
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
por: Xi, Yunjia, et al.
Publicado: (2024)
por: Xi, Yunjia, et al.
Publicado: (2024)
FINED: Feed Instance-Wise Information Need with Essential and Disentangled Parametric Knowledge from the Past
por: Du, Kounianhua, et al.
Publicado: (2024)
por: Du, Kounianhua, et al.
Publicado: (2024)
Large Language Models Make Sample-Efficient Recommender Systems
por: Lin, Jianghao, et al.
Publicado: (2024)
por: Lin, Jianghao, et al.
Publicado: (2024)
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
por: Du, Kounianhua, et al.
Publicado: (2024)
por: Du, Kounianhua, et al.
Publicado: (2024)
Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
por: Shan, Rong, et al.
Publicado: (2025)
por: Shan, Rong, et al.
Publicado: (2025)
Generative Representational Learning of Foundation Models for Recommendation
por: Zhou, Zheli, et al.
Publicado: (2025)
por: Zhou, Zheli, et al.
Publicado: (2025)
Efficiency Unleashed: Inference Acceleration for LLM-based Recommender Systems with Speculative Decoding
por: Xi, Yunjia, et al.
Publicado: (2024)
por: Xi, Yunjia, et al.
Publicado: (2024)
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models
por: Xi, Yunjia, et al.
Publicado: (2024)
por: Xi, Yunjia, et al.
Publicado: (2024)
How Can Recommender Systems Benefit from Large Language Models: A Survey
por: Lin, Jianghao, et al.
Publicado: (2023)
por: Lin, Jianghao, et al.
Publicado: (2023)
Retrieval and Distill: A Temporal Data Shift-Free Paradigm for Online Recommendation System
por: Zheng, Lei, et al.
Publicado: (2024)
por: Zheng, Lei, et al.
Publicado: (2024)
DREAM: A Dual Representation Learning Model for Multimodal Recommendation
por: Zhang, Kangning, et al.
Publicado: (2024)
por: Zhang, Kangning, et al.
Publicado: (2024)
Towards Efficient and Effective Unlearning of Large Language Models for Recommendation
por: Wang, Hangyu, et al.
Publicado: (2024)
por: Wang, Hangyu, et al.
Publicado: (2024)
Agentic Information Retrieval
por: Zhang, Weinan, et al.
Publicado: (2024)
por: Zhang, Weinan, et al.
Publicado: (2024)
DynaTree: Dynamic Agentic Retrieval Tree for Time-Sensitive News Retrieval
por: Qi, Siyuan, et al.
Publicado: (2026)
por: Qi, Siyuan, et al.
Publicado: (2026)
Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations
por: Xi, Yunjia, et al.
Publicado: (2026)
por: Xi, Yunjia, et al.
Publicado: (2026)
MassTool: A Multi-Task Search-Based Tool Retrieval Framework for Large Language Models
por: Lin, Jianghao, et al.
Publicado: (2025)
por: Lin, Jianghao, et al.
Publicado: (2025)
On-Device Recommender Systems: A Comprehensive Survey
por: Yin, Hongzhi, et al.
Publicado: (2024)
por: Yin, Hongzhi, et al.
Publicado: (2024)
Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning
por: Zhu, Jiachen, et al.
Publicado: (2025)
por: Zhu, Jiachen, et al.
Publicado: (2025)
Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation
por: Zhu, Jiachen, et al.
Publicado: (2024)
por: Zhu, Jiachen, et al.
Publicado: (2024)
A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrieval
por: Zhang, Yu, et al.
Publicado: (2025)
por: Zhang, Yu, et al.
Publicado: (2025)
Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models
por: Xi, Yunjia, et al.
Publicado: (2024)
por: Xi, Yunjia, et al.
Publicado: (2024)
AlignRec: Aligning and Training in Multimodal Recommendations
por: Liu, Yifan, et al.
Publicado: (2024)
por: Liu, Yifan, et al.
Publicado: (2024)
Retrieval-Oriented Knowledge for Click-Through Rate Prediction
por: Liu, Huanshuo, et al.
Publicado: (2024)
por: Liu, Huanshuo, et al.
Publicado: (2024)
An Automatic Graph Construction Framework based on Large Language Models for Recommendation
por: Shan, Rong, et al.
Publicado: (2024)
por: Shan, Rong, et al.
Publicado: (2024)
Stop DDoS Attacking the Research Community with AI-Generated Survey Papers
por: Lin, Jianghao, et al.
Publicado: (2025)
por: Lin, Jianghao, et al.
Publicado: (2025)
Beyond Positive History: Re-ranking with List-level Hybrid Feedback
por: Weng, Muyan, et al.
Publicado: (2024)
por: Weng, Muyan, et al.
Publicado: (2024)
From Principles to Applications: A Comprehensive Survey of Discrete Tokenizers in Generation, Comprehension, Recommendation, and Information Retrieval
por: Jia, Jian, et al.
Publicado: (2025)
por: Jia, Jian, et al.
Publicado: (2025)
Look into the Future: Deep Contextualized Sequential Recommendation
por: Zheng, Lei, et al.
Publicado: (2024)
por: Zheng, Lei, et al.
Publicado: (2024)
A Survey on Bundle Recommendation: Methods, Applications, and Challenges
por: Sun, Meng, et al.
Publicado: (2024)
por: Sun, Meng, et al.
Publicado: (2024)
Memory Assisted LLM for Personalized Recommendation System
por: Chen, Jiarui
Publicado: (2025)
por: Chen, Jiarui
Publicado: (2025)
A Survey of Retrieval Algorithms in Ad and Content Recommendation Systems
por: Zhao, Yu, et al.
Publicado: (2024)
por: Zhao, Yu, et al.
Publicado: (2024)
Ejemplares similares
-
Unleashing the Potential of Multi-Channel Fusion in Retrieval for Personalized Recommendations
por: Huang, Junjie, et al.
Publicado: (2024) -
Beyond Graph Convolution: Multimodal Recommendation with Topology-aware MLPs
por: Huang, Junjie, et al.
Publicado: (2024) -
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation
por: Chen, Jizheng, et al.
Publicado: (2024) -
D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems
por: Qin, Jiarui, et al.
Publicado: (2024) -
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation
por: Zhu, Jiachen, et al.
Publicado: (2024)