SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation

Fuente: arXiv
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Main Authors: Chen, Jingxuan, Yuen, Derek, Xie, Bin, Yang, Yuhao, Chen, Gongwei, Wu, Zhihao, Yixing, Li, Zhou, Xurui, Liu, Weiwen, Wang, Shuai, Zhou, Kaiwen, Shao, Rui, Nie, Liqiang, Wang, Yasheng, Hao, Jianye, Wang, Jun, Shao, Kun
Format: Preprint
Published: 2024
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author Chen, Jingxuan
Yuen, Derek
Xie, Bin
Yang, Yuhao
Chen, Gongwei
Wu, Zhihao
Yixing, Li
Zhou, Xurui
Liu, Weiwen
Wang, Shuai
Zhou, Kaiwen
Shao, Rui
Nie, Liqiang
Wang, Yasheng
Hao, Jianye
Wang, Jun
Shao, Kun
author_facet Chen, Jingxuan
Yuen, Derek
Xie, Bin
Yang, Yuhao
Chen, Gongwei
Wu, Zhihao
Yixing, Li
Zhou, Xurui
Liu, Weiwen
Wang, Shuai
Zhou, Kaiwen
Shao, Rui
Nie, Liqiang
Wang, Yasheng
Hao, Jianye
Wang, Jun
Shao, Kun
contents Smartphone agents are increasingly important for helping users control devices efficiently, with (Multimodal) Large Language Model (MLLM)-based approaches emerging as key contenders. Fairly comparing these agents is essential but challenging, requiring a varied task scope, the integration of agents with different implementations, and a generalisable evaluation pipeline to assess their strengths and weaknesses. In this paper, we present SPA-Bench, a comprehensive SmartPhone Agent Benchmark designed to evaluate (M)LLM-based agents in an interactive environment that simulates real-world conditions. SPA-Bench offers three key contributions: (1) A diverse set of tasks covering system and third-party apps in both English and Chinese, focusing on features commonly used in daily routines; (2) A plug-and-play framework enabling real-time agent interaction with Android devices, integrating over ten agents with the flexibility to add more; (3) A novel evaluation pipeline that automatically assesses agent performance across multiple dimensions, encompassing seven metrics related to task completion and resource consumption. Our extensive experiments across tasks and agents reveal challenges like interpreting mobile user interfaces, action grounding, memory retention, and execution costs. We propose future research directions to ease these difficulties, moving closer to real-world smartphone agent applications. SPA-Bench is available at https://ai-agents-2030.github.io/SPA-Bench/.
format Preprint
id arxiv_https___arxiv_org_abs_2410_15164
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation
Chen, Jingxuan
Yuen, Derek
Xie, Bin
Yang, Yuhao
Chen, Gongwei
Wu, Zhihao
Yixing, Li
Zhou, Xurui
Liu, Weiwen
Wang, Shuai
Zhou, Kaiwen
Shao, Rui
Nie, Liqiang
Wang, Yasheng
Hao, Jianye
Wang, Jun
Shao, Kun
Artificial Intelligence
Smartphone agents are increasingly important for helping users control devices efficiently, with (Multimodal) Large Language Model (MLLM)-based approaches emerging as key contenders. Fairly comparing these agents is essential but challenging, requiring a varied task scope, the integration of agents with different implementations, and a generalisable evaluation pipeline to assess their strengths and weaknesses. In this paper, we present SPA-Bench, a comprehensive SmartPhone Agent Benchmark designed to evaluate (M)LLM-based agents in an interactive environment that simulates real-world conditions. SPA-Bench offers three key contributions: (1) A diverse set of tasks covering system and third-party apps in both English and Chinese, focusing on features commonly used in daily routines; (2) A plug-and-play framework enabling real-time agent interaction with Android devices, integrating over ten agents with the flexibility to add more; (3) A novel evaluation pipeline that automatically assesses agent performance across multiple dimensions, encompassing seven metrics related to task completion and resource consumption. Our extensive experiments across tasks and agents reveal challenges like interpreting mobile user interfaces, action grounding, memory retention, and execution costs. We propose future research directions to ease these difficulties, moving closer to real-world smartphone agent applications. SPA-Bench is available at https://ai-agents-2030.github.io/SPA-Bench/.
title SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation
topic Artificial Intelligence
url https://arxiv.org/abs/2410.15164