most citedGenerate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion

15 citations · 25 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20248 cited

PosMLP-Video: Spatial and Temporal Relative Position Encoding for Efficient Video Recognition

Yanbin Hao, Diansong Zhou, Zhicai Wang +2

In recent years, vision Transformers and MLPs have demonstrated remarkable performance in image understanding tasks. However, their inherently dense computational operators, such a…

cs.CV2024

Model Inversion Attacks Through Target-Specific Conditional Diffusion Models

Ouxiang Li, Yanbin Hao, Zhicai Wang +4

Model inversion attacks (MIAs) aim to reconstruct private images from a target classifier's training set, thereby raising privacy concerns in AI applications. Previous GAN-based MI…

cs.CV20241 cited

Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model

Zhicai Wang, Longhui Wei, Tan Wang +5

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. Howe…

q-fin.ST20241 cited

DiffsFormer: A Diffusion Transformer on Stock Factor Augmentation

Yuan Gao, Haokun Chen, Xiang Wang +4

Machine learning models have demonstrated remarkable efficacy and efficiency in a wide range of stock forecasting tasks. However, the inherent challenges of data scarcity, includin…

cs.IR202315 cited

Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion

Zhengyi Yang, Jiancan Wu, Zhicai Wang +3

Sequential recommendation aims to recommend the next item that matches a user's interest, based on the sequence of items he/she interacted with before. Scrutinizing previous studie…