{"ID":5438636,"CreatedAt":"2026-07-01T01:17:58.482524686Z","UpdatedAt":"2026-07-03T04:20:05.427450767Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.31154","arxiv_id":"2606.31154","title":"PPT-Eval: A Benchmark for Computer-Use Agents on PowerPoint Tasks","abstract":"Creating and editing slides is a rich, multimodal activity that is ubiquitous in professional and educational settings, making it an ideal testbed for real-world computer-use agents. Microsoft PowerPoint is among the most widely adopted and feature-rich environments for presentation creation. We introduce PPT-Eval, a benchmark of 120 PowerPoint tasks across 12 files that cover both content creation and presentation editing scenarios, organized by difficulty. A central challenge in this domain is evaluation: tasks are complex, multimodal, and often admit many valid solutions. Moreover, today's agents frequently make only partial progress, which binary success metrics fail to capture. To address this, we design a robust evaluation framework to help create task-specific rubrics for PowerPoint tasks, taking inspiration from and building on past works for rubric-based evaluation. These rubrics award partial credit for intermediate steps, penalize unnecessary changes and poor aesthetics, and provide natural language feedback. This nuanced approach proves highly effective, achieving a Kendall's τ-b correlation of 0.77 with human judgments. We find that existing frontier agents still struggle with solving PowerPoint tasks, with strong models like Claude-4.5-Opus achieving only a 45% success rate and an average partial score of 57%. The benchmark is located at: https://microsoft.github.io/ppteval.","short_abstract":"Creating and editing slides is a rich, multimodal activity that is ubiquitous in professional and educational settings, making it an ideal testbed for real-world computer-use agents. Microsoft PowerPoint is among the most widely adopted and feature-rich environments for presentation creation. We introduce PPT-Eval, a b...","url_abs":"https://arxiv.org/abs/2606.31154","url_pdf":"https://arxiv.org/pdf/2606.31154v1","authors":"[\"Apurva Gandhi\",\"Vishwas Suryanarayanan\",\"Raja Hasnain Anwar\",\"Firoz Shaik\",\"Shubhang Desai\",\"Thong Q. Nguyen\",\"Muhammad Taqi Raza\",\"Vishal Chowdhary\",\"Graham Neubig\"]","published":"2026-06-30T05:26:51Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"cs.AI\"]","methods":"[\"Generative Adversarial Network\"]","has_code":false}