3 papers
cs.LG2026
Early Quantization Shrinks Codebook: A Simple Fix for Diversity-Preserving Tokenization
Wenhao Zhao, Qiran Zou, Rushi Shah +3
Vector quantization is a technique in machine learning that discretizes continuous representations into a set of discrete vectors. It is widely employed in tokenizing data represen…
cs.LG2025
Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models
Yudi Wu, Wenhao Zhao, Dianbo Liu
Generative diversity varies significantly across discrete latent generative models such as AR, MIM, and Diffusion. We propose a diagnostic framework, grounded in Information Bottle…
cs.IR2024
LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation
Bohao Wang, Feng Liu, Changwang Zhang +8
Sequential Recommenders generate recommendations based on users' historical interaction sequences. However, in practice, these collected sequences are often contaminated by noisy i…