1 citations · 1 across the 4 of their papers we have counts for
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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…
C-World: A Computer Use Agent Environment Creator
Ziqiao Xi, Shuang Liang, Qi Liu +9
To close the gap between LLM-based agents and humans in planning and reasoning, agents need large-scale, diverse environments for continuous learning -- yet building such environme…
DeliveryBench: Can Agents Earn Profit in Real World?
Lingjun Mao, Jiawei Ren, Kun Zhou +3
LLMs and VLMs are increasingly deployed as embodied agents, yet existing benchmarks largely revolve around simple short-term tasks and struggle to capture rich realistic constraint…