:: Library Catalog

Saved in:

Bibliographic Details
Main Authors:	Cui, Jiajun, Chen, Xu, Xiao, Shuai, Ju, Chen, Lan, Jinsong, Liu, Qingwen, Zhang, Wei
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval
Online Access:	https://arxiv.org/abs/2411.18631
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enhancing Cross-domain Click-Through Rate Prediction via Explicit Feature Augmentation
by: Chen, Xu, et al.
Published: (2023)

Enhancing Sequential Recommendation with World Knowledge from Large Language Models
by: Dai, Tianjie, et al.
Published: (2025)

Attribute-driven Disentangled Representation Learning for Multimodal Recommendation
by: Li, Zhenyang, et al.
Published: (2023)

DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning
by: Wang, Yifan, et al.
Published: (2024)

Unifying Search and Recommendation with Dual-View Representation Learning in a Generative Paradigm
by: Zhao, Jujia, et al.
Published: (2025)

Learning Multi-Branch Cooperation for Enhanced Click-Through Rate Prediction at Taobao
by: Chen, Xu, et al.
Published: (2024)

Category-Oriented Representation Learning for Image to Multi-Modal Retrieval
by: Cheng, Zida, et al.
Published: (2023)

M-$LLM^3$REC: A Motivation-Aware User-Item Interaction Framework for Enhancing Recommendation Accuracy with LLMs
by: Chen, Lining, et al.
Published: (2025)

On Causally Disentangled State Representation Learning for Reinforcement Learning based Recommender Systems
by: Wang, Siyu, et al.
Published: (2024)

Enhancing CTR Prediction in Recommendation Domain with Search Query Representation
by: Wang, Yuening, et al.
Published: (2024)

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation
by: Li, Hourun, et al.
Published: (2024)

Intent-aware Recommendation via Disentangled Graph Contrastive Learning
by: Wang, Yuling, et al.
Published: (2024)

Leveraging Large Language Models to Enhance Personalized Recommendations in E-commerce
by: Xu, Wei, et al.
Published: (2024)

Benefit from Rich: Tackling Search Interaction Sparsity in Search Enhanced Recommendation
by: Shi, Teng, et al.
Published: (2025)

Matryoshka Representation Learning for Recommendation
by: Lai, Riwei, et al.
Published: (2024)

Beyond Static LLM Policies: Imitation-Enhanced Reinforcement Learning for Recommendation
by: Zhang, Yi, et al.
Published: (2025)

Attention Is Not the Only Choice: Counterfactual Reasoning for Path-Based Explainable Recommendation
by: Li, Yicong, et al.
Published: (2024)

Counterfactual Multi-player Bandits for Explainable Recommendation Diversification
by: Zhang, Yansen, et al.
Published: (2025)

Learning Graph ODE for Continuous-Time Sequential Recommendation
by: Qin, Yifang, et al.
Published: (2023)

FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning
by: Zhang, Hongyu, et al.
Published: (2023)

Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models
by: Xi, Yunjia, et al.
Published: (2025)

Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation
by: Lin, Zhutian, et al.
Published: (2024)

DARLR: Dual-Agent Offline Reinforcement Learning for Recommender Systems with Dynamic Reward
by: Zhang, Yi, et al.
Published: (2025)

Heterogeneous Graph-based Framework with Disentangled Representations Learning for Multi-target Cross Domain Recommendation
by: Liu, Xiaopeng, et al.
Published: (2024)

Intent-Enhanced Data Augmentation for Sequential Recommendation
by: Chen, Shuai, et al.
Published: (2024)

Unified Generative Search and Recommendation
by: Shi, Teng, et al.
Published: (2025)

Leveraging Scene Context with Dual Networks for Sequential User Behavior Modeling
by: Chen, Xu, et al.
Published: (2025)

A Unified Search and Recommendation Framework Based on Multi-Scenario Learning for Ranking in E-commerce
by: Liu, Jinhan, et al.
Published: (2024)

Counterfactual Editing for Search Result Explanation
by: Xu, Zhichao, et al.
Published: (2023)

Causality-Inspired Fair Representation Learning for Multimodal Recommendation
by: Chen, Weixin, et al.
Published: (2023)

Enhancing Transferability and Consistency in Cross-Domain Recommendations via Supervised Disentanglement
by: Wang, Yuhan, et al.
Published: (2025)

Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples
by: Xu, Xiaoxiao, et al.
Published: (2025)

Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal Recommendations
by: Li, Jin, et al.
Published: (2025)

Continuous Input Embedding Size Search For Recommender Systems
by: Qu, Yunke, et al.
Published: (2023)

Improving Sequential Recommenders through Counterfactual Augmentation of System Exposure
by: Zhao, Ziqi, et al.
Published: (2025)

Disentangled Modeling of Preferences and Social Influence for Group Recommendation
by: Ye, Guangze, et al.
Published: (2025)

Beyond Whole Dialogue Modeling: Contextual Disentanglement for Conversational Recommendation
by: An, Guojia, et al.
Published: (2025)

Result Diversification in Search and Recommendation: A Survey
by: Wu, Haolun, et al.
Published: (2022)

CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation
by: Wang, Jun, et al.
Published: (2024)

Multi-Modal Hypergraph Enhanced LLM Learning for Recommendation
by: Guo, Xu, et al.
Published: (2025)