2 citations · 8 across the 25 of their papers we have counts for
9 papers · 1 filter
DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
Ming Ma, Jue Zhang, Fangkai Yang +4
Large language model (LLM)-based multi-agent systems are challenging to debug because failures often arise from long, branching interaction traces. The prevailing practice is to le…
AdaptFlow: Adaptive Workflow Optimization via Meta-Learning
Runchuan Zhu, Bowen Jiang, Lingrui Mei +8
Recent advances in large language models (LLMs) have sparked growing interest in agentic workflows, which are structured sequences of LLM invocations intended to solve complex task…
UFO2: The Desktop AgentOS
Chaoyun Zhang, He Huang, Chiming Ni +18
Recent Computer-Using Agents (CUAs), powered by multimodal large language models (LLMs), offer a promising direction for automating complex desktop workflows through natural langua…
Large Action Models: From Inception to Implementation
Lu Wang, Fangkai Yang, Chaoyun Zhang +15
As AI continues to advance, there is a growing demand for systems that go beyond language-based assistance and move toward intelligent agents capable of performing real-world actio…
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
Zhiyang Zhang, Xi Chen, Fangkai Yang +7
Large language model (LLM)-based AI delegates are increasingly utilized to act on behalf of users, assisting them with a wide range of tasks through conversational interfaces. Desp…
AXIS: Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents
Junting Lu, Zhiyang Zhang, Fangkai Yang +7
Multimodal large language models (MLLMs) have enabled LLM-based agents to directly interact with application user interfaces (UIs), enhancing agents' performance in complex tasks.…