AI RESEARCH
UniVLR: Unifying Text and Vision in Visual Latent Reasoning for Multimodal LLMs
arXiv CS.CL
•
ArXi:2605.11856v1 Announce Type: cross Multimodal large language models are increasingly expected to perform thinking with images, yet existing visual latent reasoning methods still rely on explicit textual chain-of-thought interleaved with visual latent tokens. This interleaved design limits efficiency and keeps reasoning fragmented across separate text and vision channels. We propose UniVLR, a unified visual latent reasoning framework that treats textual reasoning and auxiliary visual evidence as a shared visual workspace.