PosterMELD: Multi-Agent Paper-to-Poster Generation for Controllable Design Diversity with Editable Print-Ready Outputs
2026-08-03 • Artificial Intelligence
Artificial Intelligence
AI summaryⓘ
The authors present PosterMELD, a system that turns scientific papers into editable and readable posters using templates and multiple smart agents. Their method checks and fixes errors during creation to produce high-quality, editable PowerPoint and image files. Tested on over 600 papers, PosterMELD made posters that passed quality checks much more often than previous methods, while keeping costs low. The system also allows easy customization of design elements.
scientific postertemplate-based generationmulti-agent systemvision-language modelseditable outputerror correctionPowerPoint (PPTX)Portable Network Graphics (PNG)print-ready ratedesign controls
Authors
Haojie Hu, Chenhao Dang, Yaojia Liu, Hengrui Kang, Conghui He, Weijia Li
Abstract
Scientific poster construction compresses a long multimodal paper into a readable, editable canvas. Existing systems hide request-level failures by scoring only completed outputs; direct image generation is not element-editable, while coding-agent workflows are costly. PosterMELD is a template-conditioned multi-agent pipeline: capacity-aware slots guide writing before rendering, and deterministic gates plus vision-language model (VLM) review route failures to bounded repair. Each accepted request exports editable PowerPoint (PPTX) and Portable Network Graphics (PNG) artifacts; explicit design controls yield same-paper variants. Across 621 papers, Print-Ready Rate (PRR) counts requests passing geometric, readability, asset-integrity, and obvious-factual-error checks, with native editability reported separately. A frozen VLM assigns conditional Craftsmanship-Harmony-Expressiveness (CHE) scores to print-ready outputs. PosterMELD attains 81.3% PRR, 3.4 times P2P's rate and 5.2 times PosterGen's, and the highest conditional CHE among generated methods with multiple print-ready outputs. Native editability and explicit design controls are retained at a mean cost of USD 0.38 per request, 3.5% of Codex+Skill's. Code and resources are available at https://github.com/Shannon4Science/PosterMELD.