ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction.

Jianghao Lin|Bo Chen|Hangyu Wang|Yunjia Xi|Yanru Qu|Xinyi Dai|Kangning Zhang|Ruiming Tang|Yong Yu|Weinan Zhang


Anthology ID:DBLP:conf/www/LinCWXQDZTY024
Volume:Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024
Year:2024
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:3319-3330
URL:https://doi.org/10.1145/3589334.3645396
DOI:https://doi.org/10.1145/3589334.3645396
DBLP:conf/www/LinCWXQDZTY024
BibTeX:
@inproceedings{lin-2024-clickprompt, author = {Jianghao Lin and Bo Chen and Hangyu Wang and Yunjia Xi and Yanru Qu and Xinyi Dai and Kangning Zhang and Ruiming Tang and Yong Yu and Weinan Zhang}, editor = {Tat-Seng Chua and Chong-Wah Ngo and Ravi Kumar and Hady Wirawan Lauw and Roy Ka-Wei Lee}, title = {{ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction}}, booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}}, pages = {3319--3330}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3589334.3645396}, doi = {https://doi.org/10.1145/3589334.3645396} }