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Pptarena: A benchmark for agentic powerpoint editing

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it
abstract

We introduce PPTArena, a benchmark for PowerPoint editing that evaluates how agents modify real slides from natural-language instructions. Unlike benchmarks that rely on image-PDF renderings or text-to-slide generation, PPTArena features 100 decks with over 1,300 human-curated edits across 2,125 slides, spanning text, charts, animations, and professional master styles. Each edit pairs a ground-truth deck with a target rubric and is scored by two Vision-Language Model (VLM) judges: one rates instruction following from structural diffs, the other visual quality from slide images. On top of this benchmark, we present PPTPilot, a structure-aware agent that plans semantic edit sequences, routes between programmatic tools and deterministic XML operations, and verifies each result in an iterative plan-edit-check loop. PPTPilot outperforms strong VLM-based agents by more than 10 percentage points on compound, layout-sensitive, and cross-slide edits, with large gains in visual fidelity and deck-wide consistency. Despite this, all agents still struggle on long-horizon, document-scale tasks, underscoring how hard reliable PowerPoint editing remains. We publicly release our code at https://github.com/michaelofengend/PPTArena .

years

2026 4

verdicts

UNVERDICTED 4

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representative citing papers

X+Slides: Benchmarking Audience-Conditioned Slide Generation

cs.AI · 2026-06-17 · unverdicted · novelty 6.0

X+Slides is a new benchmark that measures audience-conditioned slide generation quality via 8,133 source-grounded probes across 113 topics, reporting Audience Coverage, Domain-wise Coverage, Efficiency, and Correctness on three existing systems.

LLMs Corrupt Your Documents When You Delegate

cs.CL · 2026-04-17 · unverdicted · novelty 6.0

LLMs corrupt an average of 25% of document content during long delegated editing workflows across 52 domains, even frontier models, and agentic tools do not mitigate the issue.

DeepSlide: From Artifacts to Presentation Delivery

cs.AI · 2026-04-01 · unverdicted · novelty 6.0

DeepSlide introduces a multi-agent system for full presentation preparation that matches baselines on slide quality but improves narrative flow, pacing, and script synergy via a new dual-scoreboard benchmark.

citing papers explorer

Showing 2 of 2 citing papers after filters.

  • X+Slides: Benchmarking Audience-Conditioned Slide Generation cs.AI · 2026-06-17 · unverdicted · none · ref 12 · internal anchor

    X+Slides is a new benchmark that measures audience-conditioned slide generation quality via 8,133 source-grounded probes across 113 topics, reporting Audience Coverage, Domain-wise Coverage, Efficiency, and Correctness on three existing systems.

  • DeepSlide: From Artifacts to Presentation Delivery cs.AI · 2026-04-01 · unverdicted · none · ref 24 · internal anchor

    DeepSlide introduces a multi-agent system for full presentation preparation that matches baselines on slide quality but improves narrative flow, pacing, and script synergy via a new dual-scoreboard benchmark.