2 citations · 4 across the 8 of their papers we have counts for
9 papers
Mage-VL-Cowork: A Full Training Recipe to Learn Hybrid Computer Use From Evolved Harnesses
Xiaoyi Zhang, Haoqing Wang, Xinjie Zhang +19
Effective computer-use agents (CUAs) should seamlessly combine visual GUI interaction with code and terminal execution within a single policy. We present Mage-VL-Cowork, a 4B hybri…
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…
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…
Towards Practical Real-Time Neural Video Compression
Zhaoyang Jia, Bin Li, Jiahao Li +4
We introduce a practical real-time neural video codec (NVC) designed to deliver high compression ratio, low latency and broad versatility. In practice, the coding speed of NVCs dep…
Text Grouping Adapter: Adapting Pre-trained Text Detector for Layout Analysis
Tianci Bi, Xiaoyi Zhang, Zhizheng Zhang +4
Significant progress has been made in scene text detection models since the rise of deep learning, but scene text layout analysis, which aims to group detected text instances as pa…
Slot-VLM: SlowFast Slots for Video-Language Modeling
Jiaqi Xu, Cuiling Lan, Wenxuan Xie +2
Video-Language Models (VLMs), powered by the advancements in Large Language Models (LLMs), are charting new frontiers in video understanding. A pivotal challenge is the development…
Long Video Understanding with Learnable Retrieval in Video-Language Models
Jiaqi Xu, Cuiling Lan, Wenxuan Xie +2
The remarkable natural language understanding, reasoning, and generation capabilities of large language models (LLMs) have made them attractive for application to video understandi…
Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API
Zhizheng Zhang, Wenxuan Xie, Xiaoyi Zhang +1
Recent popularity of Large Language Models (LLMs) has opened countless possibilities in automating numerous AI tasks by connecting LLMs to various domain-specific models or APIs, w…