PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control
The paper introduces PAGER, a new agent designed to improve point-precise geometric GUI control. It addresses the challenges of executing actions that require high precision in graphical user interfaces. PAGER demonstrates significant improvements in task success rates compared to existing models, establishing a new standard in this area.
- ▪PAGER aims to bridge the Semantic-Execution Gap in point-precise geometric GUI control.
- ▪The agent utilizes dependency-structured planning and pixel-level execution to enhance accuracy.
- ▪PAGER achieves a task success rate of over 62%, significantly higher than previous models.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.15963 |
| Publication time | Mon, 18 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-18T04:04:54.418Z |
| Last seen | 2026-05-18T04:04:54.418Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | O-V4TxtXFU04 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
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| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.15963 (cs) [Submitted on 15 May 2026] Title:PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control Authors:Jingxuan Wei, Xi Bai, Shan Liu, Caijun Jia, Zheng Sun, Xinglong Xu, Siyuan Li, Linzhuang Sun, Bihui Yu, Conghui He, Cheng Tan View a PDF of the paper titled PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control, by Jingxuan Wei and 10 other authors View PDF HTML (experimental) Abstract:Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet these gains largely rely on a forgiving region-tolerant paradigm, where many nearby pixels inside the same component remain valid.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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