7 papers
VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models
Zixuan Wang, Yuxin Chen, Yuqi Liu +6
Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to control signals. This "black-box" mapping forces a single forward pass…
StarVLA-: Reducing Complexity in Vision-Language-Action Systems
Jinhui Ye, Ning Gao, Senqiao Yang +7
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landscape remains highly fragmented…
Attention in Space: Functional Roles of VLM Heads for Spatial Reasoning
Xueqi Ma, Shuo Yang, Yanbei Jiang +6
Despite remarkable advances in large Vision-Language Models (VLMs), spatial reasoning remains a persistent challenge. In this work, we investigate how attention heads within VLMs c…
VisionReasoner: Unified Reasoning-Integrated Visual Perception via Reinforcement Learning
Yuqi Liu, Tianyuan Qu, Zhisheng Zhong +4
Large vision-language models exhibit inherent capabilities to handle diverse visual perception tasks. In this paper, we introduce VisionReasoner, a unified framework capable of rea…
ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay
Fanbin Lu, Zhisheng Zhong, Shu Liu +2
Training large language models (LLMs) as interactive agents for controlling graphical user interfaces (GUIs) presents a unique challenge to optimize long-horizon action sequences w…
STEVE: A Step Verification Pipeline for Computer-use Agent Training
Fanbin Lu, Zhisheng Zhong, Ziqin Wei +3
Developing AI agents to autonomously manipulate graphical user interfaces is a long challenging task. Recent advances in data scaling law inspire us to train computer-use agents wi…