User-LLM: Efficient LLM Contextualization with User Embeddings.
Lin Ning|Luyang Liu|Jiaxing Wu|Neo Wu|Devora Berlowitz|Sushant Prakash|Bradley Green|Shawn O'Banion|Jun Xie
| Anthology ID: | DBLP:conf/www/0001LWWBPGOX25 |
|---|---|
| Volume: | Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025 |
| Year: | 2025 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 1219-1223 |
| URL: | https://doi.org/10.1145/3701716.3715463 |
| DOI: | https://doi.org/10.1145/3701716.3715463 |
| DBLP: | conf/www/0001LWWBPGOX25 |
| BibTeX: |
@inproceedings{ning-2025-userllm,
author = {Lin Ning and
Luyang Liu and
Jiaxing Wu and
Neo Wu and
Devora Berlowitz and
Sushant Prakash and
Bradley Green and
Shawn O'Banion and
Jun Xie},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{User-LLM: Efficient LLM Contextualization with User Embeddings}},
booktitle = {{Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025}},
pages = {1219--1223},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3701716.3715463},
doi = {https://doi.org/10.1145/3701716.3715463}
}