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Multi-modal Recommendation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Teach Me How to Denoise: A Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration
MDE: Modality Discrimination Enhancement for Multi-modal Recommendation
Generating Negative Samples for Multi-Modal Recommendation
Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation
QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou
Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation
A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation
Towards Bridging the Cross-modal Semantic Gap for Multi-modal Recommendation
Multi-Modal Recommendation Unlearning for Legal, Licensing, and Modality Constraints
UMAIR-FPS: User-aware Multi-modal Animation Illustration Recommendation Fusion with Painting Style
Large Multi-modal Encoders for Recommendation
MM-GEF: Multi-modal representation meet collaborative filtering
Pareto Invariant Representation Learning for Multimedia Recommendation
Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation
Collaborative Recommendation Model Based on Multi-modal Multi-view Attention Network: Movie and literature cases
Multi-Modal Self-Supervised Learning for Recommendation
A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation
Multi-Modal Recommendation System with Auxiliary Information
Bootstrap Latent Representations for Multi-modal Recommendation
Self-Supervised Learning for Multimedia Recommendation
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering
DualGNN: Dual Graph Neural Network for Multimedia Recommendation
GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Mining Latent Structures for Multimedia Recommendation
Towards Multimodal MIR: Predicting individual differences from music-induced movement
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Fast Non-Local Neural Networks with Spectral Residual Learning
Multi-modal Deep Analysis for Multimedia
VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.