SOURCE-LINKED INTELLIGENCE
Attribute Token Arithmetic: Disentangled and Continuous Semantic Control for Visual Autoregressive Models
Autoregressive text-to-image generation has recently achieved remarkable progress, offering high-fidelity synthesis via a unified generative framework. However, fine-grained semantic control remains challenging due to the attribute entanglement and the misalignment between textual and fine-grained visual representations. In this paper, we introduce Attribute Token Arithmetic (ATA), a method that enables disentangled and continuous attribute control in visual autoregressive modelling. Inspired by the vector arithmetic property observed in word embeddings, ATA identifies semantic directions corr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T08:51:57.000Z
First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.