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} }