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Jiangning Zhang

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#artificial intelligence Preprint Aug 2026

Evidence-RL: Towards Evidence-intensive Visual Reasoning

Vision-Language Models (VLMs) should answer from concrete image evidence rather than language priors, dataset shortcuts, or irrelevant visual context. Existing perception-aware post-training methods encourage image use through global perturbations or attention proxies, but they do not test whether a sampled answer caus...

Haojie Huang, Xin-Lei Yu, Cheng-Ming Xu et al. · 2 citations
Preprint Aug 2026

In-Context Forcing: Uncovering Context Effects in Autoregressive Video Diffusion

In-Context Forcing is introduced, a progressive autoregressive paradigm that utilizes contexts with decreasing noise levels that enables cross-frame parallel denoising, achieving substantial inference acceleration without sacrificing performance.

Lingxiao Yang, Liu Liu, Mo-Ran Li et al. · 1 citation

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