English

PPTArena: A Benchmark for Agentic PowerPoint Editing

Computer Vision and Pattern Recognition 2025-12-09 v2 Artificial Intelligence

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.

Cite

@article{arxiv.2512.03042,
  title  = {PPTArena: A Benchmark for Agentic PowerPoint Editing},
  author = {Michael Ofengenden and Yunze Man and Ziqi Pang and Yu-Xiong Wang},
  journal= {arXiv preprint arXiv:2512.03042},
  year   = {2025}
}

Comments

Project webpage: https://ppt-arena.onrender.com/evaluation GitHub: https://github.com/michaelofengend/PPTArena

R2 v1 2026-07-01T08:06:11.878Z