Research paper
Mitigating Data Sparsity with Self-Supervised Contrastive Diffusion for Mamba-based Sequential Recommendation
ACMMM 2025 Conference Desk Rejected Submission Desk rejected
Abstract
The complete author-written abstract has not yet been supplied to this site. The verified publication metadata and primary source are available below; experimental claims should be checked against that source.
Citation
@article{2025-mamba-self-supervised,
title = {Mitigating Data Sparsity with Self-Supervised Contrastive Diffusion for Mamba-based Sequential Recommendation},
author = {Jiayang Wang and Yihan Liu and Hongji Li and Ziyi Zhuang and Junchen Fu and Linkun Dai and Joemon M. Jose and Youhua Li and Yongxin Ni},
year = {2025},
journal = {ACMMM 2025 Conference Desk Rejected Submission},
url = {https://openreview.net/search?term=Mitigating%20Data%20Sparsity%20with%20Self-Supervised%20Contrastive%20Diffusion%20for%20Mamba-based%20Sequential%20Recommendation},
}Related papers
- Bridging NIP and MLM: A Unified Meta-Learning Framework for Sequential Recommendation →
- Bridging the Gap: Teacher-Assisted Wasserstein Knowledge Distillation for Efficient Multi-Modal Recommendation →
- Crossan: Towards Efficient and Effective Adaptation of Multiple Multimodal Foundation Models for Sequential Recommendation →