9 papers
Switch-Reasoner: Learn When to Think in Multitask Mixtures via Reinforcement Learning
Yiyang Fang, Pei Fu, Jinjie Li +7
Multimodal Large Language Models (MLLMs) often follow a fixed Think-then-Answer paradigm, which is inefficient in heterogeneous multitask settings because simple inputs may not req…
DeltaV: Thinking with Visual State Updates in Unified Large Multimodal Models
Pengjie Wang, Linger Deng, Zujia Zhang +6
Current Unified Large Multimodal Models (ULMMs) support interleaved multimodal reasoning through textual reasoning and intermediate visual states, but typically generate each visua…
Xiaomi-GUI-0 Technical Report
Wanxia Cao, Chengzhen Duan, Pei Fu +29
Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions such as tapping, swiping, tex…
GAIA: A Data Flywheel System for Training GUI Test-Time Scaling Critic Models
Shaokang Wang, Pei Fu, Ruoceng Zhang +7
While Large Vision-Language Models (LVLMs) have significantly advanced GUI agents' capabilities in parsing textual instructions, interpreting screen content, and executing tasks, a…
UniTranslator: A Unified Multi-modal Framework for End-to-end In-Image Machine Translation
Jiahao Lyu, Pei Fu, Zhenhang Li +6
In-Image Machine Translation (IIMT) aims to translate scene text in an image and render the translated text back into the original regions while preserving the overall visual appea…
Enhancing Trustworthy GUI Grounding via Self-Critiqued Reinforcement Learning
Shaojie Zhang, Pei Fu, Ruoceng Zhang +8
Autonomous graphical user interface (GUI) agents rely on accurate GUI grounding, which maps language instructions to on-screen coordinates, to execute user commands. However, curre…