:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhao, Yuhan, Chen, Rui, Han, Qilong, Song, Hongtao, Chen, Li
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval
Online Access:	https://arxiv.org/abs/2412.18170
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking
by: Zhao, Yuhan, et al.
Published: (2024)

SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
by: Zhang, Chi, et al.
Published: (2024)

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
by: Kang, Li, et al.
Published: (2025)

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

Adaptive Hardness Negative Sampling for Collaborative Filtering
by: Lai, Riwei, et al.
Published: (2024)

Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users
by: Chen, Weixin, et al.
Published: (2025)

The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
by: Zhao, Yuhan, et al.
Published: (2026)

A Survey on Data-Centric Recommender Systems
by: Lai, Riwei, et al.
Published: (2024)

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

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

Enhancing CTR Prediction through Sequential Recommendation Pre-training: Introducing the SRP4CTR Framework
by: Han, Ruidong, et al.
Published: (2024)

Bootstrapping Conditional Retrieval for User-to-Item Recommendations
by: Lin, Hongtao, et al.
Published: (2025)

Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation
by: Li, Yuanzi, et al.
Published: (2026)

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

FRONTIER-RevRec: A Large-scale Dataset for Reviewer Recommendation
by: Peng, Qiyao, et al.
Published: (2025)

From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agents
by: Liu, Jiahao, et al.
Published: (2026)

SimAug: Enhancing Recommendation with Pretrained Language Models for Dense and Balanced Data Augmentation
by: Zhao, Yuying, et al.
Published: (2025)

PROMISE: Process Reward Models Unlock Test-Time Scaling Laws in Generative Recommendations
by: Guo, Chengcheng, et al.
Published: (2026)

Contextual Distillation Model for Diversified Recommendation
by: Li, Fan, et al.
Published: (2024)

MemRec: Collaborative Memory-Augmented Agentic Recommender System
by: Chen, Weixin, et al.
Published: (2026)

The Hidden Cost of Defaults in Recommender System Evaluation
by: Berling, Hannah, et al.
Published: (2025)

Mitigating Hidden Confounding Effects for Causal Recommendation
by: Zhu, Xinyuan, et al.
Published: (2022)

Unlocking the Potential of Large Language Models for Explainable Recommendations
by: Luo, Yucong, et al.
Published: (2023)

ULMRec: User-centric Large Language Model for Sequential Recommendation
by: Shao, Minglai, et al.
Published: (2024)

Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation
by: Zheng, Bowen, et al.
Published: (2024)

Gaussian Mixture Flow Matching with Domain Alignment for Multi-Domain Sequential Recommendation
by: Ye, Xiaoxin, et al.
Published: (2025)

On Mitigating Data Sparsity in Conversational Recommender Systems
by: Zhang, Sixiao, et al.
Published: (2025)

Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach
by: Chen, Jialei, et al.
Published: (2025)

CEMG: Collaborative-Enhanced Multimodal Generative Recommendation
by: Lin, Yuzhen, et al.
Published: (2025)

Enhancing Long-Term Welfare in Recommender Systems: An Information Revelation Approach
by: Zhao, Xu, et al.
Published: (2025)

GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity Prompts
by: Li, Xinyu, et al.
Published: (2024)

MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
by: Wang, Lin, et al.
Published: (2026)

Document Set Expansion with Positive-Unlabelled Learning Using Intractable Density Estimation
by: Zhang, Haiyang, et al.
Published: (2024)

Enhancing Attributed Graph Networks with Alignment and Uniformity Constraints for Session-based Recommendation
by: Zhao, Xinping, et al.
Published: (2024)

Dataset Condensation for Recommendation
by: Wu, Jiahao, et al.
Published: (2023)

DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level
by: Gao, Shen, et al.
Published: (2024)

Data Watermarking for Sequential Recommender Systems
by: Zhang, Sixiao, et al.
Published: (2024)

LLMDiRec: LLM-Enhanced Intent Diffusion for Sequential Recommendation
by: Chen, Bo-Chian, et al.
Published: (2025)

Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems
by: Wegmeth, Lukas, et al.
Published: (2024)

Semantic Gaussian Mixture Variational Autoencoder for Sequential Recommendation
by: Li, Beibei, et al.
Published: (2025)