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DecoupleMix: Decoupled Ratio Search and Convex Allocation for Scalable VLM Data Recipes

5 upvotes · 27 JUL 2026 · Jiahao Xie, Zhongbin Guo, Qianle Wang et al.

This paper introduces a systematic way to construct pretraining mixtures for Vision Language Models (VLMs) by breaking down the process into two parts: deciding which classes to combine and how to allocate data within each class. Practitioners can use this approach to improve the quality and diversity of their VLMs.

VLMsdata curationcontinual learningconvex optimizationmultimodal models