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arXiv · 2508.17345

ShortListing Model: A Streamlined SimplexDiffusion for Discrete Variable Generation

Yuxuan Song·Zhe Zhang·Yu Pei·Jingjing Gong·Qiying Yu·Zheng Zhang·Mingxuan Wang·Hao Zhou·Jingjing Liu·Wei-Ying Ma
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Abstract

Generative modeling of discrete variables is challenging yet crucial for applications in natural language processing and biological sequence design. We introduce the Shortlisting Model (SLM), a novel simplex-based diffusion model inspired by progressive candidate pruning. SLM operates on simplex centroids, reducing generation complexity and enhancing scalability. Additionally, SLM incorporates a flexible implementation of classifier-free guidance, enhancing unconditional generation performance. Extensive experiments on DNA promoter and enhancer design, protein design, character-level and large-vocabulary language modeling demonstrate the competitive performance and strong potential of SLM. Our code can be found at https://github.com/GenSI-THUAIR/SLM

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Yuxuan Song, Zhe Zhang, Yu Pei, Jingjing Gong, Qiying Yu, Zheng Zhang, Mingxuan Wang, Hao Zhou, Jingjing Liu, Wei-Ying Ma. 2025-08-24. ShortListing Model: A Streamlined SimplexDiffusion for Discrete Variable Generation. https://arxiv.org/abs/2508.17345

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