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cs.CV2026

Qwen-Image-Agent: Bridging the Context Gap in Real-World Image Generation

Zekai Zhang, Jiahao Li, Jie Zhang +18

While text-to-image (T2I) models have achieved remarkable progress, they struggle with real-world requests that are often underspecified, implicit, or dependent on up-to-date knowl…

cs.CV2026

Qwen-Image-2.0-RL Technical Report

Yixian Xu, Kaiyuan Gao, Yuxiang Chen +25

We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) to improve both the visual qu…

cs.CV2026

Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation

Jie Zhang, Xiaoyue Chen, Anzhe Chen +36

We introduce Qwen-RobotWorld, a language-conditioned video world model for embodied intelligence. With natural language as a unified action interface, it predicts physically ground…

cs.CV2025

VAEER: Visual Attention-Inspired Emotion Elicitation Reasoning

Fanhang Man, Xiaoyue Chen, Huandong Wang +3

Images shared online strongly influence emotions and public well-being. Understanding the emotions an image elicits is therefore vital for fostering healthier and more sustainable…

cs.CV2025

Progressive Supernet Training for Efficient Visual Autoregressive Modeling

Xiaoyue Chen, Yuling Shi, Kaiyuan Li +5

Visual Auto-Regressive (VAR) models significantly reduce inference steps through the "next-scale" prediction paradigm. However, progressive multi-scale generation incurs substantia…

cs.CV2025

Balanced Token Pruning: Accelerating Vision Language Models Beyond Local Optimization

Kaiyuan Li, Xiaoyue Chen, Chen Gao +2

Large Vision-Language Models (LVLMs) have shown impressive performance across multi-modal tasks by encoding images into thousands of tokens. However, the large number of image toke…