arXiv 2610.23230 · cs.CV · 2026-10-16
RAP: A Dataset for Paper-to-Poster Generation via Declarative Markup from Human-Crafted Exemplars
Haonan Han, Yukang Lin, Minliang Lin, Haoxian Tan, Jun-Yan He, Rui Yang, Zhi-Qi Cheng, Jie Hu and 2 more
meituan
In latest · #283 Added on 2026-10-22
One-line takeaway
RAP pairs 25K+ papers with posters derendered into HTML/CSS slots, enabling render-and-compare evaluation of paper-to-poster generation.
RAP 数据集收录 2.5 万多对论文与海报，把海报还原成可渲染比对的 HTML/CSS，用于论文转海报生成。
Read on arXiv PDF Hugging Face discussion Code Project page
Topics & disciplines
More on Benchmarks & data
- PremiseCheck: Efficient Fact-Checking of Human and AI Peer Reviews ▲727
- OR-License: Evaluating LLM Agents as Real-World Operations Research Practitioners ▲291
- RealCompanion: Benchmarking Human Understanding from Reasoning over Longitudinal Real-World Conversations ▲287
- GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay ▲73
- More Choices, Fewer Decisions: Ordinal-Scale Bias in JEV-like Direct-Decision Models ▲65
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.