Sequential recommendation generates personalized item rankings by estimating latent user-preference distributions from historical interactions. Although Diffusion Models (DMs) have gained prominence due to their exceptional capacity to capture complex distributions, current DM-based recommenders exhibit a critical limi...
Peng He, Yao Liu, Tong Luo et al.· ACM Transactions on Informat...· 0 citations
DiffuSent is presented, a non-auto-regressive diffusion framework that systematically formulates all ABSA subtasks as boundary denoising diffusion processes, progressively refining boundaries over noisy states, and introduces a contrastive denoising training strategy which effectively address duplicate predictions with...
S. Long, Yanglei Gan, Xuchuan Zhou· arXiv.org· 0 citations
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