6 papers
StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure
Wenyi Wu, Sibo Zhu, Kun Zhou +3
Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled increasingly capable digital agents for computer use. However, real-world tasks are o…
Planner Matters! An Efficient and Unbalanced Multi-agent Collaboration Framework for Long-horizon Planning
Wenyi Wu, Sibo Zhu, Kun Zhou +1
Language model (LM)-based agents have demonstrated promising capabilities in automating complex tasks from natural language instructions, yet they continue to struggle with long-ho…
Hybrid Self-evolving Structured Memory for GUI Agents
Sibo Zhu, Wenyi Wu, Kun Zhou +2
The remarkable progress of vision-language models (VLMs) has enabled GUI agents to interact with computers in a human-like manner. Yet real-world computer-use tasks remain difficul…
Auto-scaling Continuous Memory for GUI Agent
Wenyi Wu, Kun Zhou, Ruoxin Yuan +4
We study how to endow GUI agents with scalable memory that help generalize across unfamiliar interfaces and long-horizon tasks. Prior GUI agents compress past trajectories into tex…
Towards General Continuous Memory for Vision-Language Models
Wenyi Wu, Zixuan Song, Kun Zhou +3
Language models (LMs) and their extension, vision-language models (VLMs), have achieved remarkable performance across various tasks. However, they still struggle with complex reaso…
Causal-Copilot: An Autonomous Causal Analysis Agent
Xinyue Wang, Kun Zhou, Wenyi Wu +10
Causal analysis plays a foundational role in scientific discovery and reliable decision-making, yet it remains largely inaccessible to domain experts due to its conceptual and algo…