124 citations · 144 across the 19 of their papers we have counts for
19 papers
Diagnosing with Insights: Structured Analysis of Agent Failures via Behavioral Abstractions
Jiayi Bi, Yanjie Gao, Yuanmin Xie +4
With the proliferation of LLM agents, the ability to understand and diagnose failures in agents is essential to achieving superior effectiveness and trustworthiness. As agent failu…
Agent Skills Can Be Harmful: An Empirical Study of Skill-Induced Failures in LLM Agents
Gen Dong, Yanjie Gao, Liqun Li +3
Agent skills are the de facto mechanism for extending LLM agents with reusable guidance. A skill can shape the agent's task execution, including planning, tool use, problem-solving…
ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory
Yue Fang, Zhibang Yang, Fangkai Yang +5
Large language model (LLM) agents increasingly rely on external tools served by shared providers and accessed by heterogeneous downstream agents. Existing approaches improve tool u…
Can Large Language Models Generate Observability-Aware Code?
Yongliang Tao, Hongyu Zhang, Pengfei Gao +8
Recent advances in coding agents have enabled the generation of increasingly complex software systems. While existing evaluations primarily focus on functional correctness, product…
Computer-Using World Model
Yiming Guan, Rui Yu, John Zhang +15
Agents operating in complex software environments benefit from reasoning about the consequences of their actions, as even a single incorrect user interface (UI) operation can derai…
GUI-360: A Comprehensive Dataset and Benchmark for Computer-Using Agents
Jian Mu, Chaoyun Zhang, Chiming Ni +14
We introduce GUI-360, a large-scale, comprehensive dataset and benchmark suite designed to advance computer-using agents (CUAs). CUAs present unique challenges and is const…
UFO3: Weaving the Digital Agent Galaxy
Chaoyun Zhang, Liqun Li, He Huang +8
Large language model (LLM)-powered agents are transforming digital devices from passive tools into proactive intelligent collaborators. However, most existing frameworks remain con…
StepFly: Agentic Troubleshooting Guide Automation for Incident Diagnosis
Jiayi Mao, Liqun Li, Yanjie Gao +9
Effective incident management in large-scale IT systems relies on troubleshooting guides (TSGs), but their manual execution is slow and error-prone. While recent advances in LLMs o…
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…
API Agents vs. GUI Agents: Divergence and Convergence
Chaoyun Zhang, Shilin He, Liqun Li +5
Large language models (LLMs) have evolved beyond simple text generation to power software agents that directly translate natural language commands into tangible actions. While API-…
Large Language Model-Brained GUI Agents: A Survey
Chaoyun Zhang, Shilin He, Jiaxu Qian +10
GUIs have long been central to human-computer interaction, providing an intuitive and visually-driven way to access and interact with digital systems. The advent of LLMs, particula…
Thread: A Logic-Based Data Organization Paradigm for How-To Question Answering with Retrieval Augmented Generation
Kaikai An, Fangkai Yang, Liqun Li +10
Recent advances in retrieval-augmented generation (RAG) have substantially improved question-answering systems, particularly for factoid '5Ws' questions. However, significant chall…
Nissist: An Incident Mitigation Copilot based on Troubleshooting Guides
Kaikai An, Fangkai Yang, Junting Lu +11
Effective incident management is pivotal for the smooth operation of enterprises-level cloud services. In order to expedite incident mitigation, service teams compile troubleshooti…
UFO: A UI-Focused Agent for Windows OS Interaction
Chaoyun Zhang, Liqun Li, Shilin He +9
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a dual-agen…
TaskWeaver: A Code-First Agent Framework
Bo Qiao, Liqun Li, Xu Zhang +16
Large Language Models (LLMs) have shown impressive abilities in natural language understanding and generation, leading to their widespread use in applications such as chatbots and…
Assess and Summarize: Improve Outage Understanding with Large Language Models
Pengxiang Jin, Shenglin Zhang, Minghua Ma +13
Cloud systems have become increasingly popular in recent years due to their flexibility and scalability. Each time cloud computing applications and services hosted on the cloud are…
Incident-aware Duplicate Ticket Aggregation for Cloud Systems
Jinyang Liu, Shilin He, Zhuangbin Chen +10
In cloud systems, incidents are potential threats to customer satisfaction and business revenue. When customers are affected by incidents, they often request customer support servi…
UniParser: A Unified Log Parser for Heterogeneous Log Data
Yudong Liu, Xu Zhang, Shilin He +9
Logs provide first-hand information for engineers to diagnose failures in large-scale online service systems. Log parsing, which transforms semi-structured raw log messages into st…
Fast Outage Analysis of Large-scale Production Clouds with Service Correlation Mining
Yaohui Wang, Guozheng Li, Zijian Wang +13
Cloud-based services are surging into popularity in recent years. However, outages, i.e., severe incidents that always impact multiple services, can dramatically affect user experi…