most citedHomeBench: Evaluating LLMs in Smart Homes with Valid and Invalid Instructions Across Single and Multiple Devices

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

JarvisGUI: Towards Cross-Device GUI Agents with Dynamic Task Composition

Zixiang Chen, Yuheng Lu, Zihao Cheng +8

Real-world GUI usage frequently involves workflows that span multiple devices and platforms, requiring the transfer of intermediate results, maintenance of shared state, and coordi…

cs.CL2026

PEC-Home: Interpretation of Progressively Elliptical Commands in Smart Homes

Yingyu Shan, Zeming Liu, Silin Li +4

Recent advancements in Large Language Models (LLMs) have empowered home assistants with natural language interaction capabilities. However, current assistants overlook the progress…

cs.AI2026

DocOS: Towards Proactive Document-Guided Actions in GUI Agents

Jingjing Liu, Ziye Huang, Zihao Cheng +6

While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric knowledge from pre-training…

cs.CR2025

SafeToolBench: Pioneering a Prospective Benchmark to Evaluating Tool Utilization Safety in LLMs

Hongfei Xia, Hongru Wang, Zeming Liu +3

Large Language Models (LLMs) have exhibited great performance in autonomously calling various tools in external environments, leading to better problem solving and task automation…

cs.SE2025

RepoDebug: Repository-Level Multi-Task and Multi-Language Debugging Evaluation of Large Language Models

Jingjing Liu, Zeming Liu, Zihao Cheng +7

Large Language Models (LLMs) have exhibited significant proficiency in code debugging, especially in automatic program repair, which may substantially reduce the time consumption o…

cs.CL2025★ 1 cited

HomeBench: Evaluating LLMs in Smart Homes with Valid and Invalid Instructions Across Single and Multiple Devices

Silin Li, Yuhang Guo, Jiashu Yao +2

Large language models (LLMs) have the potential to revolutionize smart home assistants by enhancing their ability to accurately understand user needs and respond appropriately, whi…

cs.HC2025

TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments

Yuheng Lu, Qian Yu, Hongru Wang +7

Graphical User Interface (GUI) agents, which autonomously operate on digital interfaces through natural language instructions, hold transformative potential for accessibility, auto…

cs.CL2025

ToolSpectrum : Towards Personalized Tool Utilization for Large Language Models

Zihao Cheng, Hongru Wang, Zeming Liu +4

While integrating external tools into large language models (LLMs) enhances their ability to access real-time information and domain-specific services, existing approaches focus na…