SuperRS: Multi Scenario Reciprocal-Aware Dual MoE for Unified Recommendation-Search Ranking.
Zihan Xia|Chuanyu Xu|Tao Zhang|Chengfu Huo
| Anthology ID: | DBLP:conf/sigir/XiaXZH25 |
|---|---|
| Volume: | Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025 |
| Year: | 2025 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 4284-4288 |
| URL: | https://doi.org/10.1145/3726302.3731949 |
| DOI: | https://doi.org/10.1145/3726302.3731949 |
| DBLP: | conf/sigir/XiaXZH25 |
| BibTeX: |
@inproceedings{xia-2025-superrs,
author = {Zihan Xia and
Chuanyu Xu and
Tao Zhang and
Chengfu Huo},
editor = {Nicola Ferro and
Maria Maistro and
Gabriella Pasi and
Omar Alonso and
Andrew Trotman and
Suzan Verberne},
title = {{SuperRS: Multi Scenario Reciprocal-Aware Dual MoE for Unified Recommendation-Search Ranking}},
booktitle = {{Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025}},
pages = {4284--4288},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3726302.3731949},
doi = {https://doi.org/10.1145/3726302.3731949}
}