1 citations · 2 across the 11 of their papers we have counts for
7 papers · 1 filter
AndroidLens: Long-latency Evaluation with Nested Sub-targets for Android GUI Agents
Yue Cao, Yingyao Wang, Pi Bu +10
Graphical user interface (GUI) agents can substantially improve productivity by automating frequently executed long-latency tasks on mobile devices. However, existing evaluation be…
Visual-CoG: Stage-Aware Reinforcement Learning with Chain of Guidance for Text-to-Image Generation
Yaqi Li, Peng Chen, Mingyang Han +7
Despite the promising progress of recent autoregressive models in text-to-image (T2I) generation, their ability to handle multi-attribute and ambiguous prompts remains limited. To…
DeepPHY: Benchmarking Agentic VLMs on Physical Reasoning
Xinrun Xu, Pi Bu, Ye Wang +7
Although Vision Language Models (VLMs) exhibit strong perceptual abilities and impressive visual reasoning, they struggle with attention to detail and precise action planning in co…
InquireMobile: Teaching VLM-based Mobile Agent to Request Human Assistance via Reinforcement Fine-Tuning
Qihang Ai, Pi Bu, Yue Cao +8
Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on human instructions. However, the c…
Mobile-R1: Towards Interactive Capability for VLM-Based Mobile Agent via Systematic Training
Jihao Gu, Qihang Ai, Yingyao Wang +10
Vision-language model-based mobile agents have gained the ability to understand complex instructions and mobile screenshots, benefiting from reinforcement learning paradigms like G…
CombatVLA: An Efficient Vision-Language-Action Model for Combat Tasks in 3D Action Role-Playing Games
Peng Chen, Pi Bu, Yingyao Wang +9
Recent advances in Vision-Language-Action models (VLAs) have expanded the capabilities of embodied intelligence. However, significant challenges remain in real-time decision-making…
"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models
Jihao Gu, Yingyao Wang, Pi Bu +17
The evaluation of factual accuracy in large vision language models (LVLMs) has lagged behind their rapid development, making it challenging to fully reflect these models' knowledge…