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pretty_name: DECKEDIT-BENCH
license: cc-by-nc-4.0
language:
- en
- ko
tags:
- powerpoint
- pptx
- instruction-following
- document-editing
- agents
- benchmark
size_categories:
- n<1K
task_categories:
- other
configs:
- config_name: prompts
data_files: prompts.jsonl
---
# DECKEDIT-BENCH
A benchmark for **instruction-guided PowerPoint (`.pptx`) editing**. It pairs
28 real-world presentation decks with **183 natural-language editing
instructions**, organized along a **Cell × Action × Target** taxonomy and three
deck-length tiers (Short / Medium / Long).
Each instance is a `(deck, instruction)` pair: a system reads the instruction,
edits the deck, and the before/after decks are compared. The benchmark stresses
locating the right targets, decomposing multi-step instructions, compressing
repeated edits into a pattern, and **not damaging what should stay untouched**.
## Contents
```
DECKEDIT-BENCH/
├── decks/{Short,Medium,Long}/*.pptx # 28 source decks (≤10 / 11–30 / >30 slides)
├── prompts.jsonl # 183 editing instructions (one JSON / line)
├── taxonomy.json # cell + action definitions, 14 reusable templates
├── deck_info.json # per-deck metadata (size, language, topic, visuals)
├── DATASHEET.md # datasheet-for-datasets (composition, collection, cleaning)
├── TAXONOMY.md # Cell × Action × Target taxonomy + template catalog
├── THIRD_PARTY_NOTICES.md # image/figure provenance & attributions
├── LICENSE # data license (CC BY-NC 4.0)
└── CITATION.cff
```
## Prompt format (`prompts.jsonl`)
One JSON object per line:
```json
{"deck_id":"02_UTI","id":"02_UTI-01","cell":"PS","ops_per_slide":1,
"actions":["REPLACE"],"derived_from":"U-01",
"intent":"…what this instance tests…","text":"…instruction sent to the system…"}
```
- `text` — the instruction handed to the editing system.
- `cell` ∈ `{ES, EC, PS, PC}` · `actions` ⊆ `{ADD, DELETE, REPLACE, SLIDE}`.
- `derived_from` — a universal template id (`U-xx`, see `taxonomy.json`) or `"deck-specific"`.
See **TAXONOMY.md** for definitions.
## Quickstart
```python
import json
prompts = [json.loads(l) for l in open("prompts.jsonl", encoding="utf-8")]
info = {d["id"]: d for d in json.load(open("deck_info.json", encoding="utf-8"))["decks"]}
p = prompts[0]
deck_path = info[p["deck_id"]]["path"] # e.g. "decks/Short/01_CausalAGI.pptx"
# 1. open deck_path, 2. apply p["text"] with your system, 3. diff before/after.
```
## Coverage
| | total | breakdown |
|---|---|---|
| Decks | **28** | Short 9 · Medium 12 · Long 7 |
| Prompts | **183** | Short 54 · Medium 81 · Long 48 |
| Cells | — | ES 17 · EC 57 · PS 87 · PC 22 |
| Deck languages | — | en 21 · ko 7 (translate targets also span ja/fr/es/zh) |
Full Cell × Action matrix and known imbalances are in **DATASHEET.md**.
## Notes on the decks
- **Full resolution.** The `.pptx` files keep original-resolution media (~1 GB
total) and are distributed via Git LFS / the dataset host.
- **Privacy.** Every deck was scrubbed of author/coauthoring/comment PII; see
**DATASHEET.md → Preprocessing/cleaning**.
- **Provenance.** Embedded figures in paper-review decks, and the replacement
images in `11_FourthIndustryStartup`, are credited in **THIRD_PARTY_NOTICES.md**.
## License & citation
Data is released under **CC BY-NC 4.0** (see `LICENSE`). If you use
DECKEDIT-BENCH, please cite it — see `CITATION.cff`.
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