Generative Enhanced Modeling: A Collaborative Framework for Enhancing User Representations via Semantic ID.
Li Li|Wei Xu|Yu Cheng|Jianbin Lin|Can Ye
| Anthology ID: | DBLP:conf/sigir/LiXCLY26 |
|---|---|
| Volume: | Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026 |
| Year: | 2026 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 4732-4736 |
| URL: | https://doi.org/10.1145/3805712.3808448 |
| DOI: | https://doi.org/10.1145/3805712.3808448 |
| DBLP: | conf/sigir/LiXCLY26 |
| BibTeX: |
@inproceedings{li-2026-generative,
author = {Li Li and
Wei Xu and
Yu Cheng and
Jianbin Lin and
Can Ye},
editor = {Hannah Bast and
Alistair Moffat and
Falk Scholer and
Marc Najork and
Min Zhang and
Hannah Bast and
Marc Najork and
Min Zhang},
title = {{Generative Enhanced Modeling: A Collaborative Framework for Enhancing User Representations via Semantic ID}},
booktitle = {{Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026}},
pages = {4732--4736},
publisher = {ACM},
year = {2026},
url = {https://doi.org/10.1145/3805712.3808448},
doi = {https://doi.org/10.1145/3805712.3808448}
}