Multimodal pretraining, adaptation, and generation for recommendation: A survey

Q Liu, J Zhu, Y Yang, Q Dai, Z Du, XM Wu… - Proceedings of the 30th …, 2024 - dl.acm.org
Personalized recommendation serves as a ubiquitous channel for users to discover
information tailored to their interests. However, traditional recommendation models primarily …

Unified Visual Preference Learning for User Intent Understanding

Y Wen, S Chen, Y Tian, W Guan, P Wang… - Proceedings of the 17th …, 2024 - dl.acm.org
In the world of E-Commerce, the core task is to understand the personalized preference from
various kinds of heterogeneous information, such as textual reviews, item images and …

End-to-end training of Multimodal Model and ranking Model

X Deng, L Xu, X Li, J Yu, E Xue, Z Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
Traditional recommender systems heavily rely on ID features, which often encounter
challenges related to cold-start and generalization. Modeling pre-extracted content features …

Intuitive Smart Creative Designing using Computer Vision

LV D'souza, MK Rajendran - SoutheastCon 2023, 2023 - ieeexplore.ieee.org
In the era of digital advertisements, the relevancy of advertisements and preferences of the
end customer are key in determining the success of a Campaign. Understanding the …