Pre-training for Recommendation Unlearning
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Guoxuan, Xia, Lianghao, Huang, Chao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LightGNN: Simple Graph Neural Network for Recommendation
by: Chen, Guoxuan, et al.
Published: (2025)
by: Chen, Guoxuan, et al.
Published: (2025)
GraphPro: Graph Pre-training and Prompt Learning for Recommendation
by: Yang, Yuhao, et al.
Published: (2023)
by: Yang, Yuhao, et al.
Published: (2023)
SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation
by: Liu, Yuxi, et al.
Published: (2024)
by: Liu, Yuxi, et al.
Published: (2024)
DiffGraph: Heterogeneous Graph Diffusion Model
by: Li, Zongwei, et al.
Published: (2025)
by: Li, Zongwei, et al.
Published: (2025)
RecDiff: Diffusion Model for Social Recommendation
by: Li, Zongwei, et al.
Published: (2024)
by: Li, Zongwei, et al.
Published: (2024)
Machine Unlearning for Recommendation Systems: An Insight
by: Sachdeva, Bhavika, et al.
Published: (2024)
by: Sachdeva, Bhavika, et al.
Published: (2024)
A Comprehensive Survey on Self-Supervised Learning for Recommendation
by: Ren, Xubin, et al.
Published: (2024)
by: Ren, Xubin, et al.
Published: (2024)
CURE:Circuit-Aware Unlearning for LLM-based Recommendation
by: Chen, Ziheng, et al.
Published: (2026)
by: Chen, Ziheng, et al.
Published: (2026)
Graph Augmentation for Recommendation
by: Zhang, Qianru, et al.
Published: (2024)
by: Zhang, Qianru, et al.
Published: (2024)
Not All Candidates are Created Equal: A Heterogeneity-Aware Approach to Pre-ranking in Recommender Systems
by: Tong, Pengfei, et al.
Published: (2026)
by: Tong, Pengfei, et al.
Published: (2026)
SSLRec: A Self-Supervised Learning Framework for Recommendation
by: Ren, Xubin, et al.
Published: (2023)
by: Ren, Xubin, et al.
Published: (2023)
Movie Recommendation with Poster Attention via Multi-modal Transformer Feature Fusion
by: Xia, Linhan, et al.
Published: (2024)
by: Xia, Linhan, et al.
Published: (2024)
MixRec: Heterogeneous Graph Collaborative Filtering
by: Xia, Lianghao, et al.
Published: (2024)
by: Xia, Lianghao, et al.
Published: (2024)
Representation Learning with Large Language Models for Recommendation
by: Ren, Xubin, et al.
Published: (2023)
by: Ren, Xubin, et al.
Published: (2023)
Lightweight yet Efficient: An External Attentive Graph Convolutional Network with Positional Prompts for Sequential Recommendation
by: Zhang, Jinyu, et al.
Published: (2025)
by: Zhang, Jinyu, et al.
Published: (2025)
PSLF: A PID Controller-incorporated Second-order Latent Factor Analysis Model for Recommender System
by: Wang, Jialiang, et al.
Published: (2024)
by: Wang, Jialiang, et al.
Published: (2024)
Learning to Fast Unrank in Collaborative Filtering Recommendation
by: Zhao, Junpeng, et al.
Published: (2025)
by: Zhao, Junpeng, et al.
Published: (2025)
Graph Foundation Models for Recommendation: A Comprehensive Survey
by: Wu, Bin, et al.
Published: (2025)
by: Wu, Bin, et al.
Published: (2025)
Lightweight yet Fine-grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-account Sequential Recommendation
by: Zhang, Jinyu, et al.
Published: (2024)
by: Zhang, Jinyu, et al.
Published: (2024)
Enhancing Recommendation with Denoising Auxiliary Task
by: Liu, Pengsheng, et al.
Published: (2024)
by: Liu, Pengsheng, et al.
Published: (2024)
LightRAG: Simple and Fast Retrieval-Augmented Generation
by: Guo, Zirui, et al.
Published: (2024)
by: Guo, Zirui, et al.
Published: (2024)
Disentangled Contrastive Collaborative Filtering
by: Ren, Xubin, et al.
Published: (2023)
by: Ren, Xubin, et al.
Published: (2023)
Knowledge-Enhanced Recommendation with User-Centric Subgraph Network
by: Liu, Guangyi, et al.
Published: (2024)
by: Liu, Guangyi, et al.
Published: (2024)
Modeling Behavioral Intensity and Transitions for Generative Recommendation
by: Yang, Wenxuan, et al.
Published: (2026)
by: Yang, Wenxuan, et al.
Published: (2026)
Test-Time Scaling Strategies for Generative Retrieval in Multimodal Conversational Recommendations
by: Hsu, Hung-Chun, et al.
Published: (2025)
by: Hsu, Hung-Chun, et al.
Published: (2025)
DiffGRM: Diffusion-based Generative Recommendation Model
by: Liu, Zhao, et al.
Published: (2025)
by: Liu, Zhao, et al.
Published: (2025)
Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation
by: Huang, Tianhao, et al.
Published: (2024)
by: Huang, Tianhao, et al.
Published: (2024)
Pre-train and Fine-tune: Recommenders as Large Models
by: Jiang, Zhenhao, et al.
Published: (2025)
by: Jiang, Zhenhao, et al.
Published: (2025)
Ripple Knowledge Graph Convolutional Networks For Recommendation Systems
by: Li, Chen, et al.
Published: (2023)
by: Li, Chen, et al.
Published: (2023)
PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
by: Yang, Weiqin, et al.
Published: (2024)
by: Yang, Weiqin, et al.
Published: (2024)
Item Cluster-aware Prompt Learning for Session-based Recommendation
by: Yang, Wooseong, et al.
Published: (2024)
by: Yang, Wooseong, et al.
Published: (2024)
Talos: Optimizing Top-$K$ Accuracy in Recommender Systems
by: Zhang, Shengjia, et al.
Published: (2026)
by: Zhang, Shengjia, et al.
Published: (2026)
DKINet: Medication Recommendation via Domain Knowledge Informed Deep Learning
by: Liu, Sicen, et al.
Published: (2023)
by: Liu, Sicen, et al.
Published: (2023)
Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn)
by: Bhattacharya, Moumita, et al.
Published: (2024)
by: Bhattacharya, Moumita, et al.
Published: (2024)
DeGRe: Dense-supervised Generative Reranking for Recommendation
by: Song, Chaotian, et al.
Published: (2026)
by: Song, Chaotian, et al.
Published: (2026)
BEAR: Towards Beam-Search-Aware Optimization for Recommendation with Large Language Models
by: Yang, Weiqin, et al.
Published: (2026)
by: Yang, Weiqin, et al.
Published: (2026)
LLaTTE: Scaling Laws for Multi-Stage Sequence Modeling in Large-Scale Ads Recommendation
by: Xiong, Lee, et al.
Published: (2026)
by: Xiong, Lee, et al.
Published: (2026)
Impression-Aware Recommender Systems
by: Maurera, Fernando B. Pérez, et al.
Published: (2023)
by: Maurera, Fernando B. Pérez, et al.
Published: (2023)
Enhancing CTR Prediction in Recommendation Domain with Search Query Representation
by: Wang, Yuening, et al.
Published: (2024)
by: Wang, Yuening, et al.
Published: (2024)
LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation
by: Jiang, Shali, et al.
Published: (2026)
by: Jiang, Shali, et al.
Published: (2026)
Similar Items
-
LightGNN: Simple Graph Neural Network for Recommendation
by: Chen, Guoxuan, et al.
Published: (2025) -
GraphPro: Graph Pre-training and Prompt Learning for Recommendation
by: Yang, Yuhao, et al.
Published: (2023) -
SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation
by: Liu, Yuxi, et al.
Published: (2024) -
DiffGraph: Heterogeneous Graph Diffusion Model
by: Li, Zongwei, et al.
Published: (2025) -
RecDiff: Diffusion Model for Social Recommendation
by: Li, Zongwei, et al.
Published: (2024)