PSPA-Bench: A Personalized Benchmark for Smartphone GUI Agent
- URL: http://arxiv.org/abs/2603.29318v1
- Date: Tue, 31 Mar 2026 06:37:12 GMT
- Title: PSPA-Bench: A Personalized Benchmark for Smartphone GUI Agent
- Abstract summary: PSPA-Bench is the benchmark dedicated to evaluating personalization in smartphone GUI agents.<n> PSPA-Bench comprises over 12,855 personalized instructions aligned with real-world user behaviors.<n>Results reveal that current methods perform poorly under personalized settings.
- Score: 32.14146282263351
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Smartphone GUI agents execute tasks by operating directly on app interfaces, offering a path to broad capability without deep system integration. However, real-world smartphone use is highly personalized: users adopt diverse workflows and preferences, challenging agents to deliver customized assistance rather than generic solutions. Existing GUI agent benchmarks cannot adequately capture this personalization dimension due to sparse user-specific data and the lack of fine-grained evaluation metrics. To address this gap, we present PSPA-Bench, the benchmark dedicated to evaluating personalization in smartphone GUI agents. PSPA-Bench comprises over 12,855 personalized instructions aligned with real-world user behaviors across 10 representative daily-use scenarios and 22 mobile apps, and introduces a structure-aware process evaluation method that measures agents' personalized capabilities at a fine-grained level. Through PSPA-Bench, we benchmark 11 state-of-the-art GUI agents. Results reveal that current methods perform poorly under personalized settings, with even the strongest agent achieving limited success. Our analysis further highlights three directions for advancing personalized GUI agents: (1) reasoning-oriented models consistently outperform general LLMs, (2) perception remains a simple yet critical capability, and (3) reflection and long-term memory mechanisms are key to improving adaptation. Together, these findings establish PSPA-Bench as a foundation for systematic study and future progress in personalized GUI agents.
Related papers
- ProBench: Benchmarking GUI Agents with Accurate Process Information [15.519853892615272]
We introduce ProBench, a comprehensive benchmark with over 200 challenging GUI tasks covering widely-used scenarios.<n>We extend our dataset to include Process-related Task and design a specialized evaluation method.<n>Our evaluation of advanced GUI agents reveals significant limitations for real-world GUI scenarios.
arXiv Detail & Related papers (2025-11-12T09:49:31Z) - MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment [63.62778707277929]
MobileGUI-RL is a scalable framework that trains GUI agent in online environment.<n>It synthesizes a curriculum of learnable tasks through self-exploration and filtering.<n>It adapts GRPO to GUI navigation with trajectory-aware advantages and composite rewards.
arXiv Detail & Related papers (2025-07-08T07:07:53Z) - Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents [15.303188467166752]
We present CogniGUI, a cognitive framework developed to overcome limitations by enabling adaptive learning for GUI automation resembling human-like behavior.<n>To assess the generalization and adaptability of agent systems, we introduce ScreenSeek, a comprehensive benchmark that includes multi application navigation, dynamic state transitions, and cross interface coherence.<n> Experimental results demonstrate that CogniGUI surpasses state-of-the-art methods in both the current GUI grounding benchmarks and our newly proposed benchmark.
arXiv Detail & Related papers (2025-06-22T06:30:52Z) - PersonaAgent: When Large Language Model Agents Meet Personalization at Test Time [87.99027488664282]
PersonaAgent is a framework designed to address versatile personalization tasks.<n>It integrates a personalized memory module and a personalized action module.<n>Test-time user-preference alignment strategy ensures real-time user preference alignment.
arXiv Detail & Related papers (2025-06-06T17:29:49Z) - Look Before You Leap: A GUI-Critic-R1 Model for Pre-Operative Error Diagnosis in GUI Automation [83.92224427735859]
We introduce a pre-operative critic mechanism that provides effective feedback prior to the actual execution.<n>We develop a reasoning-bootstrapping based data collection pipeline to create a GUI-Critic-Train and a GUI-Critic-Test.<n>Our model offers significant advantages in critic accuracy compared to current MLLMs.
arXiv Detail & Related papers (2025-06-05T04:12:36Z) - AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning [82.42421823672954]
AgentCPM-GUI is built for robust and efficient on-device GUI interaction.<n>Our training pipeline includes grounding-aware pre-training to enhance perception.<n>AgentCPM-GUI achieves state-of-the-art performance on five public benchmarks.
arXiv Detail & Related papers (2025-06-02T07:30:29Z) - GUI-Xplore: Empowering Generalizable GUI Agents with One Exploration [22.814882629516635]
We introduce GUI-Xplore, a dataset meticulously designed to enhance cross-application and cross-task generalization.<n>To fully exploit GUI-Xplore's unique features, we propose Xplore-Agent, a GUI agent framework that combines Action-aware GUI Modeling with Graph-Guided Environment Reasoning.
arXiv Detail & Related papers (2025-03-22T09:30:37Z) - UI-TARS: Pioneering Automated GUI Interaction with Native Agents [58.18100825673032]
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions.<n>In the OSWorld benchmark, UI-TARS achieves scores of 24.6 with 50 steps and 22.7 with 15 steps, outperforming Claude (22.0 and 14.9 respectively)
arXiv Detail & Related papers (2025-01-21T17:48:10Z) - Zero-Shot Prompting Approaches for LLM-based Graphical User Interface Generation [53.1000575179389]
We propose a Retrieval-Augmented GUI Generation (RAGG) approach, integrated with an LLM-based GUI retrieval re-ranking and filtering mechanism.<n>In addition, we adapt Prompt Decomposition (PDGG) and Self-Critique (SCGG) for GUI generation.<n>Our evaluation, which encompasses over 3,000 GUI annotations from over 100 crowd-workers with UI/UX experience, shows that SCGG, in contrast to PDGG and RAGG, can lead to more effective GUI generation.
arXiv Detail & Related papers (2024-12-15T22:17:30Z) - ASSISTGUI: Task-Oriented Desktop Graphical User Interface Automation [30.693616802332745]
This paper presents a novel benchmark, AssistGUI, to evaluate whether models are capable of manipulating the mouse and keyboard on the Windows platform in response to user-requested tasks.
We propose an advanced Actor-Critic framework, which incorporates a sophisticated GUI driven by an AI agent and adept at handling lengthy procedural tasks.
arXiv Detail & Related papers (2023-12-20T15:28:38Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.