Image de couverture de livre

Simple but Efficient: A Multi-Scenario Nearline Retrieval Framework for Recommendation on Taobao

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ma, Yingcai, Wang, Ziyang, Yan, Yuliang, Wu, Jian, Jiang, Yuning, Li, Longbin, Chen, Wen, Huang, Jianhang
Format:	Preprint
Publié:	2024
Sujets:	Information Retrieval
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

PI2I: A Personalized Item-Based Collaborative Filtering Retrieval Framework
par: Wang, Shaoqing, et autres
Publié: (2026)

Retrieval-GRPO: A Multi-Objective Reinforcement Learning Framework for Dense Retrieval in Taobao Search
par: Liu, Xingxian, et autres
Publié: (2025)

Beyond Existing Retrievals: Cross-Scenario Incremental Sample Learning Framework
par: Wang, Tao, et autres
Publié: (2025)

TBGRecall: A Generative Retrieval Model for E-commerce Recommendation Scenarios
par: Liang, Zida, et autres
Publié: (2025)

RecGPT-Mobile: On-Device Large Language Models for User Intent Understanding in Taobao Feed Recommendation
par: Zhang, Bin, et autres
Publié: (2026)

Parallel Latent Reasoning for Sequential Recommendation
par: Tang, Jiakai, et autres
Publié: (2026)

Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insights
par: Sheng, Xiang-Rong, et autres
Publié: (2024)

LEAPS: An LLM-Empowered Adaptive Plugin in Taobao AI Search
par: Wang, Lei, et autres
Publié: (2026)

RankGR: Rank-Enhanced Generative Retrieval with Listwise Direct Preference Optimization in Recommendation
par: Fu, Kairui, et autres
Publié: (2026)

Large Language Model based Long-tail Query Rewriting in Taobao Search
par: Peng, Wenjun, et autres
Publié: (2023)

A Generative Re-ranking Model for List-level Multi-objective Optimization at Taobao
par: Meng, Yue, et autres
Publié: (2025)

Learning Multi-Branch Cooperation for Enhanced Click-Through Rate Prediction at Taobao
par: Chen, Xu, et autres
Publié: (2024)

Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
par: Tang, Jiakai, et autres
Publié: (2025)

Towards Personalized Federated Multi-Scenario Multi-Task Recommendation
par: Ding, Yue, et autres
Publié: (2024)

Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark
par: Li, Xiaopeng, et autres
Publié: (2024)

A Unified Search and Recommendation Framework Based on Multi-Scenario Learning for Ranking in E-commerce
par: Liu, Jinhan, et autres
Publié: (2024)

Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models
par: Xi, Yunjia, et autres
Publié: (2025)

TranSUN: A Preemptive Paradigm to Eradicate Retransformation Bias Intrinsically from Regression Models in Recommender Systems
par: Yu, Jiahao, et autres
Publié: (2025)

Multi-Scenario User Profile Construction via Recommendation Lists
par: Zhang, Hui, et autres
Publié: (2026)

Unleashing the Potential of Multi-Channel Fusion in Retrieval for Personalized Recommendations
par: Huang, Junjie, et autres
Publié: (2024)

Internalizing Multi-Agent Reasoning for Accurate and Efficient LLM-based Recommendation
par: Wu, Yang, et autres
Publié: (2026)

NoteLLM: A Retrievable Large Language Model for Note Recommendation
par: Zhang, Chao, et autres
Publié: (2024)

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation
par: Zhai, Penglong, et autres
Publié: (2025)

M2Rec: Multi-scale Mamba for Efficient Sequential Recommendation
par: Zhang, Qianru, et autres
Publié: (2025)

Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation
par: Fu, Dongqi, et autres
Publié: (2026)

HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders
par: Yuan, Kun, et autres
Publié: (2026)

Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and Method
par: Liu, Ze, et autres
Publié: (2024)

MACRec: a Multi-Agent Collaboration Framework for Recommendation
par: Wang, Zhefan, et autres
Publié: (2024)

Efficient Multi-task Prompt Tuning for Recommendation
par: Bai, Ting, et autres
Publié: (2024)

On Practical Diversified Recommendation with Controllable Category Diversity Framework
par: Zhang, Tao, et autres
Publié: (2024)

RaSeRec: Retrieval-Augmented Sequential Recommendation
par: Zhao, Xinping, et autres
Publié: (2024)

M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation
par: Zhu, Jiachen, et autres
Publié: (2024)

MTGR: Industrial-Scale Generative Recommendation Framework in Meituan
par: Han, Ruidong, et autres
Publié: (2025)

Counterfactual Multi-player Bandits for Explainable Recommendation Diversification
par: Zhang, Yansen, et autres
Publié: (2025)

A Comprehensive Survey on Retrieval Methods in Recommender Systems
par: Huang, Junjie, et autres
Publié: (2024)

Optimizing Recall or Relevance? A Multi-Task Multi-Head Approach for Item-to-Item Retrieval in Recommendation
par: Zhang, Jiang, et autres
Publié: (2025)

Accelerating Generative Recommendation via Simple Categorical User Sequence Compression
par: Liu, Qijiong, et autres
Publié: (2026)

KARMA: Knowledge-Action Regularized Multimodal Alignment for Personalized Search at Taobao
par: Sun, Zhi, et autres
Publié: (2026)

From Principles to Applications: A Comprehensive Survey of Discrete Tokenizers in Generation, Comprehension, Recommendation, and Information Retrieval
par: Jia, Jian, et autres
Publié: (2025)

Retrieve-then-Adapt: Retrieval-Augmented Test-Time Adaptation for Sequential Recommendation
par: Tang, Xing, et autres
Publié: (2026)