Author

Rong-Hao Xian

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Preprint Sep 2026

Pay More Attention To Text In High-Resolution MLLMs

Failures of high-resolution MLLMs are commonly attributed to a visual problem, motivating zooming, cropping, and related visual interventions to recover fine-grained evidence or suppress interference. Yet recent studies suggest that relevant visual evidence is already encoded in intermediate representations, indicating...

Z. Mao, Wen-Zhuo Zhao, Xian-Jie Liu et al. · 1 citation

Jul 2026

Is It Time for the Renaissance of Salient Object Detection in the Era of MLLMs?

FOCUS couples top-down Bayesian-surprise calibration of protocol-conditioned foreground granularity with bottom-up propagation of MLLMs evidence over entity-centric perceptual manifolds induced by self-supervised features, yielding coherent object extents as prompts for a general segmenter.

Wen-Zhuo Zhao, Xiuzhi Li, Z. Mao et al. · arXiv.org · 1 citation

Jul 2026

Thinking Once Is Enough: Intermediate-Layer Evidence Routing for High-Resolution VQA

Thinking-Once is proposed, a training-free, single-visual-pass evidence-routing method that reconstructs question-conditioned attention at this window, preserves core entity tokens and compact background context, and routes this evidence to later layers without extra visual encoding.

Z. Mao, Xian-Jie Liu, Tian-Yu Meng et al. · arXiv.org · 0 citations