PPTArena: A Benchmark for Agentic PowerPoint Editing

Michael Ofengenden, Yunze Man, Ziqi Pang, Yu-Xiong Wang
12/2/2025
cs.CVcs.AI

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Abstract

We introduce PPTArena, a benchmark for PowerPoint editing that measures reliable modifications to real slides under natural-language instructions. In contrast to image-PDF renderings or text-to-slide generation, PPTArena focuses on in-place editing across 100 decks, 2125 slides, and over 800 targeted edits covering text, charts, tables, animations, and master-level styles. Each case includes a ground-truth deck, a fully specified target outcome, and a dual VLM-as-judge pipeline that separately scores instruction following and visual quality using both structural diffs and slide images. Building on this setting, we propose PPTPilot, a structure-aware slide-editing agent that plans semantic edit sequences, routes between high-level programmatic tools and deterministic XML operations for precise control, and verifies outputs through an iterative plan-edit-check loop against task-specific constraints. In our experiments, PPTPilot outperforms strong proprietary agents and frontier VLM systems by over 10 percentage points on compound, layout-sensitive, and cross-slide edits, with particularly large gains in visual fidelity and deck-wide consistency. Despite these improvements, existing agents still underperform on long-horizon, document-scale tasks in PPTArena, highlighting the remaining challenges in reliable PPT editing.

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Cite this paper

@article{ofengenden2025pptarena,
  title  = {PPTArena: A Benchmark for Agentic PowerPoint Editing},
  author = {Michael Ofengenden and Yunze Man and Ziqi Pang and Yu-Xiong Wang},
  year   = {2025},
  eprint = {2512.03042},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.03042v2}
}

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