Unlocking Scaling Law in Industrial Recommendation Systems with a Three-step Paradigm based Large User Model.
Bencheng Yan|Shilei Liu|Zhiyuan Zeng|Zihao Wang|Yizhen Zhang|Yujin Yuan|Langming Liu|Jiaqi Liu|Di Wang|Wenbo Su|Pengjie Wang|Jian Xu|Bo Zheng
| Anthology ID: | DBLP:conf/wsdm/YanLZW0YLLWS00026 |
|---|---|
| Volume: | Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026 |
| Year: | 2026 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 798-807 |
| URL: | https://doi.org/10.1145/3773966.3777970 |
| DOI: | https://doi.org/10.1145/3773966.3777970 |
| DBLP: | conf/wsdm/YanLZW0YLLWS00026 |
| BibTeX: |
@inproceedings{yan-2026-unlocking,
author = {Bencheng Yan and
Shilei Liu and
Zhiyuan Zeng and
Zihao Wang and
Yizhen Zhang and
Yujin Yuan and
Langming Liu and
Jiaqi Liu and
Di Wang and
Wenbo Su and
Pengjie Wang and
Jian Xu and
Bo Zheng},
title = {{Unlocking Scaling Law in Industrial Recommendation Systems with a Three-step Paradigm based Large User Model}},
booktitle = {{Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026}},
pages = {798--807},
publisher = {ACM},
year = {2026},
url = {https://doi.org/10.1145/3773966.3777970},
doi = {https://doi.org/10.1145/3773966.3777970}
}