11 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…
DynamicBench: Evaluating Real-Time Report Generation in Large Language Models
Jingyao Li, Hao Sun, Zile Qiao +5
Traditional benchmarks for large language models (LLMs) typically rely on static evaluations through storytelling or opinion expression, which fail to capture the dynamic requireme…
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…
MoTCoder: Elevating Large Language Models with Modular of Thought for Challenging Programming Tasks
Jingyao Li, Pengguang Chen, Bin Xia +2
Large Language Models (LLMs) have showcased impressive capabilities in handling straightforward programming tasks. However, their performance tends to falter when confronted with m…
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…