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From the 1 of 9 linked papers with an AI index.

collaborators

9 papers

eess.AS2026

Qwen-Audio-VAE Technical Report

Ziyue Jiang, Dake Guo, Zekai Zhang +11

Qwen-Audio-VAE is a low‑bitrate, fast‑encoding continuous audio autoencoder that produces compact latent representations for scalable text‑to‑audio generation, using a causal encod…

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-Image-Bench: From Generation to Creation in Text-to-Image Evaluation

Niantong Li, Guangzheng Hu, Weixu Qiao +35

Text-to-Image generation has evolved from basic image synthesis into a frequently used core capability in professional creative workflows, where simple text-image alignment can no…

cs.CV2026

Qwen-Image-Flash: Beyond Objective Design

Tianhe Wu, Kun Yan, Zikai Zhou +21

Few-step distillation has become an effective strategy for accelerating advanced visual generative models, yet prior work has largely focused on distillation objectives. In this wo…

cs.CV2026

Qwen-Image-VAE-2.0 Technical Report

Zekai Zhang, Deqing Li, Kuan Cao +27

We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…