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cs.CV2026

DeepSketcher: Internalizing Visual Manipulation for Multimodal Reasoning

Chi Zhang, Haibo Qiu, Qiming Zhang +3

The "thinking with images" paradigm represents a pivotal shift in the reasoning of Vision Language Models (VLMs), moving from text-dominant chain-of-thought to image-interactive re…

cs.CV2025

Learning When to Look: A Disentangled Curriculum for Strategic Perception in Multimodal Reasoning

Siqi Yang, Zilve Gao, Haibo Qiu +5

Multimodal Large Language Models (MLLMs) demonstrate significant potential but remain brittle in complex, long-chain visual reasoning tasks. A critical failure mode is "visual forg…

cs.CV2025

Counting Hallucinations in Diffusion Models

Shuai Fu, Jian Zhou, Qi Chen +7

Diffusion probabilistic models (DPMs) have demonstrated remarkable progress in generative tasks, such as image and video synthesis. However, they still often produce hallucinated s…

cs.CV2025

Perceptual-Evidence Anchored Reinforced Learning for Multimodal Reasoning

Chi Zhang, Haibo Qiu, Qiming Zhang +6

Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced the reasoning capabilities of Large Language Models (LLMs) and is now being applied to Vision-Langu…

cs.CV2025

Towards Better & Faster Autoregressive Image Generation: From the Perspective of Entropy

Xiaoxiao Ma, Feng Zhao, Pengyang Ling +6

In this work, we first revisit the sampling issues in current autoregressive (AR) image generation models and identify that image tokens, unlike text tokens, exhibit lower informat…

cs.CV2025

STAGE: Stable and Generalizable GRPO for Autoregressive Image Generation

Xiaoxiao Ma, Haibo Qiu, Guohui Zhang +4

Reinforcement learning has recently been explored to improve text-to-image generation, yet applying existing GRPO algorithms to autoregressive (AR) image models remains challenging…