LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction.

Xin Song|Xiaochen Li|Jinxin Hu|Hong Wen|Zulong Chen|Yu Zhang|Xiaoyi Zeng|Jing Zhang


Anthology ID:DBLP:conf/sigir/SongLHWCZZZ25
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:2843-2847
URL:https://doi.org/10.1145/3726302.3730228
DOI:https://doi.org/10.1145/3726302.3730228
DBLP:conf/sigir/SongLHWCZZZ25
BibTeX:
@inproceedings{song-2025-lrea, author = {Xin Song and Xiaochen Li and Jinxin Hu and Hong Wen and Zulong Chen and Yu Zhang and Xiaoyi Zeng and Jing Zhang}, editor = {Nicola Ferro and Maria Maistro and Gabriella Pasi and Omar Alonso and Andrew Trotman and Suzan Verberne}, title = {{LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction}}, 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 = {2843--2847}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3726302.3730228}, doi = {https://doi.org/10.1145/3726302.3730228} }