# DECKEDIT-BENCH — Datasheet Following the *Datasheets for Datasets* structure (Gebru et al., 2021). ## Motivation Instruction-guided document editing is largely evaluated on plain text or single-shape image edits. Real presentation editing is harder: instructions are under-specified, targets must be located among many shapes, edits repeat across slides, and a good system must change only what was asked while preserving everything else. DECKEDIT-BENCH provides real decks and natural-language instructions to measure these abilities, with an explicit axis for **preservation** (non-target damage) alongside instruction-following accuracy. ## Composition - **Instances.** 183 `(deck, instruction)` pairs over 28 `.pptx` decks. - **Deck tiers** (by slide count): Short ≤10 (9 decks), Medium 11–30 (12), Long >30 (7). Largest deck: 50 slides. - **Instructions per tier:** Short 54 · Medium 81 · Long 48. - **Cells:** ES 17 · EC 57 · PS 87 · PC 22 (see TAXONOMY.md). - **Languages:** source decks are en (21) / ko (7); some instructions ask for translation into en/ko/ja/fr/es/zh. - **Domains** (28 decks): AI/ML/Speech-NLP research (12), STEM lecture & engineering (4), Humanities & general (4), Business reports (3), Architecture/Urban/Visual (3), Medical/Bio (2). - **Visuals:** decks variously contain pictures, tables, and charts; per-deck inventory is in `deck_info.json` (`visuals`). - **Two fully-synthetic decks** (`02_RemoteWorkSurvey`, `09_ApexAnalytics`) are chart-heavy fixtures authored for this benchmark. Each instance carries: `deck_id`, `id`, `cell`, `ops_per_slide`, `actions`, `derived_from` (template id or `deck-specific`), `intent`, `text`. ### Known imbalances / limitations - REPLACE accounts for ~75 % of actions; ADD/DELETE/SLIDE are sparser. - `SLIDE` actions appear only in PS cells; ES/EC/PC × SLIDE = 0. - `slide-mgmt` (add/delete/duplicate slide) is barely tested. - Multi-action instructions (≥2 distinct actions) are rare. - Domain skew toward AI/Speech research (~43 % of decks); legal/finance/sales/ medical-chart are under-represented — an external-validity caveat. - Not every instruction is deterministically checkable: ~75 % are (text/color/font/chart-attr/background); translate/summarize/"important parts" require an LLM/vision judge. ## Collection process Decks are real lecture, seminar, paper-review, proposal, and report presentations contributed by their authors (with permission), plus two synthetic chart decks. Instructions were authored for this benchmark to cover the Cell × Action × Target space; 92 derive from 14 reusable templates (`taxonomy.json`), 91 are deck-specific. No model outputs are included in the released data. ## Preprocessing / cleaning / anonymization All decks were sanitized for personal and third-party data. PII in `.pptx` hides in **non-visible metadata layers**; every layer below was scrubbed and the result re-verified (0 residual names / emails / template watermarks across all 28 decks): 1. **Document properties** — `docProps/core.xml`, `app.xml`: `creator`, `lastModifiedBy`, `title`, `subject`, `keywords`, `Company`, `Manager` cleared. 2. **Comment / coauthor records** — `ppt/authors.xml`, `ppt/commentAuthors.xml`: real author names anonymized to `Author A/B/…` (5 decks), initials blanked. 3. **Coauthoring revision history** — `ppt/changesInfos/changesInfo*.xml`: `chgData name=` author names anonymized (4 decks). 4. **Embedded emails** — real addresses replaced with `example.*` placeholders. `11_FourthIndustryStartup` was originally built on a commercial third-party template; it was **rebuilt copyright-clean**: original text and styling preserved verbatim, the template's full-slide background and all raster images removed, template-vendor watermarks stripped, and slide imagery replaced with license-clean Unsplash photos (then downsized to 1920 px). Its instruction targets (team identifier, author list, four category labels, a replaceable image, the startup-pitch body) are preserved, so its prompts behave as before. ## Uses Intended for evaluating instruction-guided `.pptx` editing systems (instruction-following accuracy, target localization, pattern compression, and content preservation). Not intended as training data for, or evaluation of, deck *generation* from scratch. The decks reflect their source domains and languages and should not be treated as a representative sample of all presentations. ## Distribution Released as static files (decks + `prompts.jsonl` + `taxonomy.json` + `deck_info.json` + docs). Decks retain original-resolution media (~1 GB total) and require Git LFS or a large-file dataset host. License: **CC BY-NC 4.0** (`LICENSE`); third-party image/figure attributions in `THIRD_PARTY_NOTICES.md`. This v1 release is **data only** — the evaluation/judge harness is not included. ## Maintenance When adding decks or instructions: update `deck_info.json`; add the instructions to the per-deck source and regenerate `prompts.jsonl` / `taxonomy.json`; re-run the PII scrub and coverage audit. The benchmark is intended to grow toward the gaps listed under *Known imbalances*.