From Transient Prompts to Persistent Control: Scientific Poster Generation via Recursive Semantic-Geometric Contracts

Runze Li, Yukun Zhao, Can Xu, Yucheng Shen, Shuaiqiang Wang +3 more
9/15/2026
cs.AI

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Abstract

Scientific poster generation distills a multimodal paper into a single-page visual artifact, forcing strict trade-offs between informational coverage and readability under a fixed spatial budget. Existing methods pass plans as transient prompts and validate individual stages in isolation. This strategy causes requirements to drift across content and layout modules, and previous checks to be silently invalidated. We introduce PosterVisor, a control framework that shifts poster generation from transient prompts to persistent control. An Orchestrator grounds rubrics in the paper and visual assets, compiling them into a Semantic-Geometric Contract (SGC) that binds claims and sources to required visuals, budgets, and spatial commitments. Only fully instantiated records become executable assertions; other usable requirements remain soft guidance. Recursive Contract Enforcement (RCE) dynamically triggers checks across stages as evidence emerges. Crucially, during repairs, RCE rechecks affected checkpoint states, preventing repair-induced regressions from propagating silently. We instantiate PosterVisor in HTML/CSS and editable PPTX generators. On the 100-paper Paper2Poster benchmark, PosterVisor-PPT improves observed mean poster-grounded QA accuracy over PosterGen (64.47% vs. 58.53%) and is preferred by human judges in 72.5% of non-tied pairwise comparisons (95% CI, 61.6-83.4%). A secondary 30-paper study also yields higher VLM Overall and PaperQuiz means. These results support rubric-compiled contracts and stage-conditioned enforcement for controllable poster synthesis.

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Cite this paper

@article{li2026from,
  title  = {From Transient Prompts to Persistent Control: Scientific Poster Generation via Recursive Semantic-Geometric Contracts},
  author = {Runze Li and Yukun Zhao and Can Xu and Yucheng Shen and Shuaiqiang Wang and Jianmin Wu and Lingyong Yan and Dawei Yin},
  year   = {2026},
  eprint = {2609.17326},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2609.17326v1}
}

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