PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks
Unified multimodal models (UMMs) have shown impressive capabilities in generating natural images and supporting multimodal reasoning. However, their potential in supporting computer-use planning tasks, which are closely related to our lives, remain underexplored. Image generation and editing in computer-use tasks require capabilities like spatial reasoning and procedural understanding, and it is still unknown whether UMMs have these capabilities to finish these tasks or not. Therefore, we propose PlanViz, a new benchmark designed to evaluate image generation and editing for computer-use tasks. To achieve the goal of our evaluation, we focus on sub-tasks which frequently involve in daily life and require planning steps. Specifically, three new sub-tasks are designed: route planning, work diagramming, and web&UI displaying. We address challenges in data quality ensuring by curating human-annotated questions and reference images, and a quality control process. For challenges of comprehensive and exact evaluation, a task-adaptive score, PlanScore, is proposed. The score helps understanding the correctness, visual quality and efficiency of generated images. Through experiments, we highlight key limitations and opportunities for future research on this topic.
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Junxian Li
claimed_verified
2026-02-09T08:29:28.216Z
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Junxian Li
Duke-de-Artois
user
Duke-de-Artois
698959b9beecc443208d26c3
Kai Liu
698959b9beecc443208d26c4
Leyang Chen
698959b9beecc443208d26c5
Weida Wang
claimed_verified
2026-02-09T08:29:30.996Z
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Weida Wang
weidawang
user
weidawang
698959b9beecc443208d26c6
Zhixin Wang
698959b9beecc443208d26c7
Jiaqi Xu
698959b9beecc443208d26c8
Fan Li
698959b9beecc443208d26c9
Renjing Pei
698959b9beecc443208d26ca
Linghe Kong
698959b9beecc443208d26cb
Yulun Zhang
PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks
Unified multimodal models (UMMs) have shown impressive capabilities in generating natural images and supporting multimodal reasoning. However, their potential in supporting computer-use planning tasks, which are closely related to our lives, remain underexplored. Image generation and editing in computer-use tasks require capabilities like spatial reasoning and procedural understanding, and it is still unknown whether UMMs have these capabilities to finish these tasks or not. Therefore, we propose PlanViz, a new benchmark designed to evaluate image generation and editing for computer-use tasks. To achieve the goal of our evaluation, we focus on sub-tasks which frequently involve in daily life and require planning steps. Specifically, three new sub-tasks are designed: route planning, work diagramming, and web&UI displaying. We address challenges in data quality ensuring by curating human-annotated questions and reference images, and a quality control process. For challenges of comprehensive and exact evaluation, a task-adaptive score, PlanScore, is proposed. The score helps understanding the correctness, visual quality and efficiency of generated images. Through experiments, we highlight key limitations and opportunities for future research on this topic.
PlanViz benchmark evaluates unified multimodal models' capabilities in computer-use planning tasks through route planning, work diagramming, and web&UI displaying sub-tasks with a task-adaptive scoring system.
unified multimodal models image generation image editing spatial reasoning procedural understanding computer-use planning PlanViz route planning work diagramming web&UI displaying PlanScore