Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors.
Binzong Geng|Zhaoxin Huan|Xiaolu Zhang|Yong He|Liang Zhang|Fajie Yuan|Jun Zhou|Linjian Mo
| Anthology ID: | DBLP:conf/sigir/GengHZHZYZM24 |
|---|---|
| Volume: | Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024 |
| Year: | 2024 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 2311-2315 |
| URL: | https://doi.org/10.1145/3626772.3657974 |
| DOI: | https://doi.org/10.1145/3626772.3657974 |
| DBLP: | conf/sigir/GengHZHZYZM24 |
| BibTeX: |
@inproceedings{geng-2024-breaking,
author = {Binzong Geng and
Zhaoxin Huan and
Xiaolu Zhang and
Yong He and
Liang Zhang and
Fajie Yuan and
Jun Zhou and
Linjian Mo},
editor = {Grace Hui Yang and
Hongning Wang and
Sam Han and
Claudia Hauff and
Guido Zuccon and
Yi Zhang},
title = {{Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors}},
booktitle = {{Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024}},
pages = {2311--2315},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3626772.3657974},
doi = {https://doi.org/10.1145/3626772.3657974}
}