224 citations · 360 across the 36 of their papers we have counts for
11 papers · 1 filter
Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model
Senqiao Yang, Kaichen Zhang, Zhaoyang Jia +20
Standard vision-language models (VLMs) suffer from Moravec's paradox: they excel at complex offline visual reasoning but struggle with simple streaming perception tasks and process…
Generative Video Compression with Adaptive Score Distillation
Naifu Xue, Zhaoyang Jia, Haosen Li +7
Diffusion models provide strong generative capabilities for video compression at ultra-low bitrates. Existing diffusion-based video codecs adapt base models originally developed fo…
Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing
Xinjie Zhang, Peng Zhang, Shicheng Zheng +21
Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to…
Ultra-Fast Neural Video Compression
Jiahao Li, Wenxuan Xie, Zhaoyang Jia +4
While neural video codecs (NVCs) have demonstrated superior compression ratio, their prohibitive computational complexity remains a critical barrier to real-world deployment. This…
An Efficient Streaming Video Understanding Framework with Agentic Control
Jinming Liu, Jianguo Huang, Zhaoyang Jia +7
Streaming video requires handling dynamic information density under strict latency budgets. Yet, existing methods typically employ static strategies, such as fixed memory compressi…
Efficient 3D Content Reconstruction and Generation
Jiahao Li
Automatic 3D content creation seeks to replace labor-intensive modeling and scanning pipelines with systems that can synthesize or recover 3D assets directly from text or images. I…
Generative Video Compression with One-Dimensional Latent Representation
Zihan Zheng, Zhaoyang Jia, Naifu Xue +7
Recent advancements in generative video codec (GVC) typically encode video into a 2D latent grid and employ high-capacity generative decoders for reconstruction. However, this para…
Clue Matters: Leveraging Latent Visual Clues to Empower Video Reasoning
Kaixin zhang, Xiaohe Li, Jiahao Li +4
Multi-modal Large Language Models (MLLMs) have significantly advanced video reasoning, yet Video Question Answering (VideoQA) remains challenging due to its demand for temporal cau…
Compression as Adaptation: Implicit Visual Representation with Diffusion Foundation Models
Zongyu Guo, Jiajun He, Zhaoyang Jia +6
Modern visual generative models acquire rich visual knowledge through large-scale training, yet existing visual representations (such as pixels, latents, or tokens) remain external…
Efficient Autoregressive Video Diffusion with Dummy Head
Hang Guo, Zhaoyang Jia, Jiahao Li +5
The autoregressive video diffusion model has recently gained considerable research interest due to its causal modeling and iterative denoising. In this work, we identify that the m…
InfiniteWeb: Scalable Web Environment Synthesis for GUI Agent Training
Ziyun Zhang, Zezhou Wang, Xiaoyi Zhang +4
GUI agents that interact with graphical interfaces on behalf of users represent a promising direction for practical AI assistants. However, training such agents is hindered by the…