Against Opacity: Explainable AI and Large Language Models for Effective Digital Advertising-Reference-Cited by-同舟云学术

Against Opacity: Explainable AI and Large Language Models for Effective Digital Advertising

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Yang Qi¹^ORCID,Ongpin Marlo²^ORCID,Nikolenko Sergey¹^ORCID,Huang Alfred³^ORCID,Farseev Aleksandr²^ORCID

Affiliation:

1. ITMO University, Saint Petersburg, Russian Fed.

2. SoMin.ai Research, Singapore, Singapore

3. SoMin.ai Research, Singapore, Russian Fed.

Funder

Russian Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612817

Reference39 articles.

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3. Anton Alekseev , Elena Tutubalina , Sejeong Kwon , and Sergey Nikolenko . 2022. Near-Zero-Shot Suggestion Mining with a Little Help from WordNet . In Analysis of Images, Social Networks and Texts . Springer International Publishing , Cham , 23--36. Anton Alekseev, Elena Tutubalina, Sejeong Kwon, and Sergey Nikolenko. 2022. Near-Zero-Shot Suggestion Mining with a Little Help from WordNet. In Analysis of Images, Social Networks and Texts. Springer International Publishing, Cham, 23--36.

4. J. Bergstra , R. Bardenet , Y. Bengio , and B. Kégl . 2011 . Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems , Vol. 24 . Curran Associates, Inc. J. Bergstra, R. Bardenet, Y. Bengio, and B. Kégl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems, Vol. 24. Curran Associates, Inc.

5. Multi-view Personality Profiling Based on Longitudinal Data

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