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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
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content="HyperNeRF handles topological variations by modeling a family of shapes in a higher-dimensional space, thereby producing more realistic renderings and more accurate geometric reconstructions.">
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/* 为背景颜色改变添加过渡效果 */
}
.navbar.scrolled {
background-color: #209CEE;
}
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float: left;
}
.navbar li a {
display: block;
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text-align: center;
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</head>
<body>
<ul class="navbar" id="navbar">
<li><a href="#home">
<!-- <img src="assets/poster.png" alt="Home" style="height:30px; width:30px; vertical-align:middle; margin-right:5px;"> -->
<strong>🎓Paper2Poster</strong> </a>
</li>
</ul>
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<section class="hero">
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<div class="container">
<div class="columns is-centered">
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<img src="static/images/logo.svg" alt="HyperNeRF"/>
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</div>
<div class="container has-text-centered">
<h1 class="title is-2 publication-title">
<br>
<!-- <img src="assets/poster.png" alt="Home" style="height:40px; width:40px; vertical-align:middle; margin-right:5px;"> -->
🎓Paper2Poster<br>Towards Multimodal Poster Automation from Scientific Papers
</h1>
<p class="subtitle is-4">NeurIPS 2025 D&B</p>
<div class="is-size-5 publication-authors">
<span class="author-block">
<sup>1,3</sup><a href="https://scholar.google.com/citations?user=f90pZOYAAAAJ&hl=en">Wei Pang</a><sup>†</sup>,</span>
<span class="author-block">
<sup>2</sup><a href="https://qhlin.me">Kevin Qinghong Lin</a><sup>✉</sup><sup>†</sup>,</span>
<span class="author-block">
<sup>1</sup><a href="https://edward-jianqaq.github.io/">Xiangru Jian</a><sup>†</sup>,</span>
<span class="author-block">
<sup>1,3</sup><a href="https://cs.uwaterloo.ca/~xihe/">Xi He</a><sup>✉</sup>,</span>
<span class="author-block">
<sup>2</sup><a href="https://scholar.google.com/citations?user=kPxa2w0AAAAJ&hl=en">Philip Torr</a>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>University of Waterloo</span>
<span class="author-block"><sup>2</sup>University of Oxford</span>
<span class="author-block"><sup>3</sup>Vector Institute</span>
</div>
† Equal Contribution ✉ Corresponding Authors
<div class="column has-text-centered">
<div class="publication-links">
<!-- PDF Link. -->
<!-- <span class="link-block">
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class="external-link button is-normal is-rounded is-dark">
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<a href="https://arxiv.org/abs/2505.21497" class="external-link button is-normal is-rounded is-dark">
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<i class="ai ai-arxiv"></i>
</span>
<span>Paper</span>
</a>
</span>
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<a href="https://github.com/Paper2Poster/Paper2Poster"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
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<span>Code</span>
</a>
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<a href="https://huggingface.co/datasets/Paper2Poster/Paper2Poster"
class="external-link button is-normal is-rounded is-dark">
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</span>
<span>Datasets</span>
</a>
</span>
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<a href="https://huggingface.co/spaces/camel-ai/Paper2Poster"
class="external-link button is-normal is-rounded is-dark">
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<i class="ai ai-academia"></i>
</span>
<span>Huggingface Demo</span>
</a>
</span>
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class="external-link button is-normal is-rounded is-dark">
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<span class="author-block"><b></b></span>
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</div>
</div>
</section>
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">🤩 Paper2Poster for Paper2Poster</h2>
</div>
</div>
<!-- </br> -->
<CENter>
<img src="./assets/teaser.jpeg" alt="">
</CENter>
</div>
</div>
<br>
</section>
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">TL;DR</h2>
<div class="content has-text-centered">
<p>
We address <strong>How to create a poster from a paper</strong> and <strong>How to evaluate poster</strong>.
</p>
</div>
</div>
</div>
<!-- </br> -->
<CENter>
<img src="./assets/overall.png" alt="">
</CENter>
</div>
</div>
<br>
</section>
<section class="hero teaser">
<div class="hero-body">
<div class="columns is-centered">
<h2 class="title is-3">Can AI assistants create a well-designed Poster given a Paper?</h2>
</div>
<div class="container is-max-desktop">
<div class="columns is-vcentered">
<!-- Left: Paper -->
<div class="column has-text-centered">
<img src="./assets/example/paper.png" alt="Paper" style="height: 400px;">
<p class="caption" style="text-align: center; margin-top: 10px;"><strong>Inputs: </strong><a href="https://arxiv.org/pdf/2210.15986">Paper</a> (a PDF)</p>
</div>
<!-- Arrow -->
<!-- <div class="column has-text-centered">
<img src="./assets/right.png" alt="Arrow" style="width: 40px;">
</div> -->
<!-- Right: Poster -->
<div class="column has-text-centered">
<img src="./assets/example/gt_poster.png" alt="Poster" style="height: 400px; max-width: none;">
<p class="caption" style="text-align: center; margin-top: 10px;"><strong>Outputs: </strong><a href="https://neurips.cc/media/PosterPDFs/NeurIPS%202022/61269.png?t=1669788855.791561">Poster</a> (designed by author)</p>
</p>
</div>
</div>
</div>
</div>
</section>
<section class="hero teaser">
<div class="hero-body">
<div class="columns is-centered">
<h2 class="title is-3">How GPT-4o or Open-source Multi-agents behave?</h2>
</div>
<div class="container is-max-desktop">
<!-- 第一行 -->
<div class="columns is-vcentered">
<div class="column has-text-centered">
<img src="./assets/example/4o_image.png" alt="GPT-4o Image" style="height: 400px; max-width: none;">
<p class="caption" style="text-align: center; margin-top: 10px;"><strong>Poster generated by GPT-4o-image</strong></p>
</div>
<div class="column has-text-centered">
<img src="./assets/example/4o_html.png" alt="GPT-4o HTML" style="height: 400px; max-width: none;">
<p class="caption" style="text-align: center; margin-top: 10px;"><strong>Poster generated by GPT-4o-html</strong></p>
</div>
</div>
<!-- 第二行 -->
<div class="columns is-vcentered">
<div class="column has-text-centered">
<img src="./assets/example/ppt_agent.png" alt="PPT-Agent" style="height: 400px; max-width: none;">
<p class="caption" style="text-align: center; margin-top: 10px;"><strong>Poster generated by <a href="https://github.com/icip-cas/PPTAgent">PPTAgent</a></strong></p>
</div>
<div class="column has-text-centered">
<img src="./assets/example/owl.png" alt="OWL" style="height: 400px; max-width: none;">
<p class="caption" style="text-align: center; margin-top: 10px;"><strong>Poster generated by <a href="https://github.com/camel-ai/owl">🦉OWL</a></strong></p>
</div>
</div>
<figcaption class="caption" style="margin-bottom: 1px; text-align: center;">
<strong>GPT-4o-image</strong> visually acceptable layouts at first glance, but closer inspection <strong>zoom-in-region</strong> reveals impaired text rendering, leading to poor readability of fine-grained details.
<strong>GPT-4o-HTML</strong> and <strong>OWL</strong> generate blog-like, text-dense posters that suffer from low visual readability.
<strong>PPTAgent</strong> struggles with layout control, often resulting in missing panels.
</figcaption>
</section>
<section class="hero teaser">
<div class="hero-body">
<div class="columns is-centered">
<h2 class="title is-3">Poster Generated by PosterAgent</h2>
</div>
<div class="container is-max-desktop">
<div class="columns is-vcentered">
<div class="column has-text-centered">
<img src="./assets/example/poster_agent_red.png" alt="PosterAgent" style="height: 600px; max-width: none;">
<p class="caption" style="text-align: center; margin-top: 10px;">In contrast, <strong>PosterAgent</strong> generates structurally coherent and readable posters while using significantly fewer words.</p>
</div>
</div>
</div>
</div>
</section>
<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered">
<h2 class="title is-3">What are the Challenges?</h2>
</div>
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<div class="content has-text-justified">
<p>
<!-- VideoGUI focuses on professional and novel software like PR, AE for video editing, and Stable Diffusion, Runway for visual creation.
We source tasks from high-quality instructional videos, with annotators replicating these to reproduce effects;
We provide detailed annotations with planning procedures and recorded actions for hierarchical evaluation. -->
<ul>
<li><strong>Long-Context Long-Horizon Task:</strong> Scientific papers span multiple pages and thousands of words. Summarizing key insights while preserving coherence demands hierarchical understanding and selective abstraction. The complexity further necessitates long-horizon reasoning and multiple iterative interactions, making the task especially challenging.</li>
<li><strong>Interleaved Multimodal Inputs:</strong> Papers integrate numerous figures, tables, and charts, each semantically linked to the surrounding text. Successful poster generation demands the ability to extract, interpret, and align these multimodal elements in a contextually appropriate manner.</li>
<li><strong>Layout-aware Multimodal Outputs:</strong> Unlike tasks focused solely on text (e.g., blog) or vision, poster generation requires producing interleaved text–image outputs within a constrained spatial layout. This necessitates joint reasoning over language, visual content, and layout to prevent overflow, imbalance, and logical misalignment.</li> </ul>
</p>
</div>
</div>
</div>
</div>
</div>
</br>
</section>
<section class="hero teaser">
<div class="hero-body">
<div class="columns is-centered">
<h2 class="title is-3">How to create poster 👉 PosterAgent</h2>
</div>
<div class="container is-max-desktop">
<center>
<div class="columns is-centered">
<div class="column is-full">
<figure style="width: 100%;">
<img src="./assets/posteragent.png" alt="stat" width="90%">
</figure>
</div>
</div>
</center>
<figcaption class="caption" style="margin-bottom: 1px; text-align: center;">
<strong>A Top-down, visual-in-the-loop, efficient multi-agent pipeline.</strong>
</figcaption>
<strong>(a) Parser</strong> distills the paper into a structured asset library;
the <strong>(b) Planner</strong> aligns text–visual pairs into a binary‐tree layout that preserves reading order and spatial balance;
and the <strong>(c) Painter-Commentor</strong> loop refines each panel by executing rendering code and using VLM feedback to eliminate overflow and ensure alignment.
</div>
</div>
</section>
<section class="hero teaser">
<div class="hero-body">
<div class="columns is-centered">
<h2 class="title is-3">How to evaluate poster 👉 PaperQuiz</h2>
</div>
<div class="container is-max-desktop">
<center>
<div class="columns is-centered">
<div class="column is-full">
<figure style="width: 100%;">
<img src="./assets/paperquiz.png" alt="stat" width="90%">
</figure>
</div>
</div>
</center>
<figcaption class="caption" style="margin-bottom: 1px; text-align: center;">
<strong>A Good poster should convey core paper content visually.</strong>
</figcaption>
<strong>Left:</strong> We automatically generate multiple-choice questions from each paper using an LLM (o3), forming the our PaperQuiz evaluation.
<strong>Right:</strong> In PaperQuiz, we simulate multiple reader by allowing VLMs—representing different expertise levels (e.g., student, professor)—to read each generated poster and answer the quiz.
The poster that achieves the highest average score is considered the most effective in conveying the paper's content.
</div>
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</section>
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<h2 class="title is-3">Abstract</h2>
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<p>
Academic poster generation is a crucial yet challenging task in scientific communication, requiring the compression of long-context interleaved documents into a single, visually coherent page. To address this challenge, we introduce the first benchmark and metric suite for poster generation, which pairs recent conference papers with author-designed posters and evaluates outputs on (i) Visual Quality—semantic alignment with human posters, (ii) Textual Coherence—language fluency, (iii) Holistic Assessment—six fine-grained aesthetic and informational criteria scored by a VLM-as-judge, and notably (iv) PaperQuiz—the poster’s ability to convey core paper content as measured by VLMs answering generated quizzes. Building on this benchmark, we propose PosterAgent, a top-down, visualin-the-loop multi-agent pipeline: the (a) Parser distills the paper into a structured asset library; the (b) Planner aligns text–visual pairs into a binary-tree layout that preserves reading order and spatial balance; and the (c) Painter–Commenter loop refines each panel by executing rendering code and using VLM feedback to eliminate overflow and ensure alignment. In our comprehensive evaluation, we find that GPT-4o outputs—though visually appealing at first glance—often exhibit noisy text and poor PaperQuiz scores, and we find that reader engagement is the primary aesthetic bottleneck, as human-designed posters rely largely on visual semantics to convey meaning. Our fully open-source Paper2Poster pipeline outperforms GPT-4o–based systems across nearly all metrics while consuming 87% fewer tokens. These findings chart clear directions for the next generation of fully automated poster-generation models.
</p>
</div>
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</section>
<section class="hero teaser">
<div class="hero-body">
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<h2 class="title is-3">Data Statistic</h2>
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(a) Word cloud illustrating the diversity of research topics. (b) Textual Token statistics and Figure count statistics for input papers vs. posters provided by authors.
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</section>
<section class="hero teaser">
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<h2 class="title is-3">Main Results on Existing Solutions</h2>
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<figure style="width: 100%;">
<img src="./assets/table1.png" alt="stat" width="90%">
<figcaption class="caption" style="margin-bottom: 1px; text-align: center;">
<strong>Detailed evaluation of Paper2Poster.</strong>
</figcaption>
</figure>
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</center>
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</div>
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<figure style="width: 100%;">
<img src="./assets/table2.png" alt="stat" width="90%">
<figcaption class="caption" style="margin-bottom: 1px; text-align: center;">
<strong>PaperQuiz evaluation on Paper2Poster.</strong>
</figcaption>
</figure>
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</center>
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</section>
<section class="hero teaser">
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<figure style="width: 100%;">
<img src="./assets/Tab 3.png" alt="Efficiency & Cost analysis" width="90%">
<figcaption class="caption" style="margin-bottom: 1px; text-align: center;">
<strong>Efficiency & Cost analysis demonstrating PosterAgent’s strong efficiency and low API cost.</strong>
</figcaption>
</figure>
</div>
</div>
</center>
</div>
</div>
</section>
<style>
.poster-carousel {
display: flex;
overflow-x: auto;
scroll-behavior: smooth;
gap: 20px;
padding: 20px;
cursor: grab;
}
.poster-carousel:active {
cursor: grabbing;
}
.poster-item {
flex: 0 0 auto;
width: 45%;
text-align: center;
}
.poster-item img {
height: 500px;
object-fit: contain;
}
.caption-small {
margin-top: 8px;
font-size: 14px;
color: #555;
}
.caption-large {
text-align: center;
font-weight: bold;
font-size: 16px;
margin-top: 20px;
}
</style>
<div class="hero teaser">
<div class="hero-body">
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<h2 class="title is-3">More Examples</h2>
</div>
<div class="poster-carousel" id="carousel">
<div class="poster-item">
<img src="./assets/supp_examples/Conformal Semantic Keypoint Detection with Statistical Guarantees/gt.png" alt="gt poster">
<p class="caption-small">Generated by Author</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Conformal Semantic Keypoint Detection with Statistical Guarantees/4o_image.png" alt="GPT-4o Image">
<p class="caption-small">Generated by GPT-4o-image</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Conformal Semantic Keypoint Detection with Statistical Guarantees/4o_html.png" alt="GPT-4o Html">
<p class="caption-small">Generated by GPT-4o-html</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Conformal Semantic Keypoint Detection with Statistical Guarantees/ppt_agent.png" alt="PPT Agent">
<p class="caption-small">Generated by PPTAgent</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Conformal Semantic Keypoint Detection with Statistical Guarantees/owl.png" alt="OWL">
<p class="caption-small">Generated by OWL</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Conformal Semantic Keypoint Detection with Statistical Guarantees/ours.png" alt="PosterAgent">
<p class="caption-small">Generated by PostAgent</p>
</div>
</div>
<p class="caption-large">
Case-1: <a href="https://arxiv.org/pdf/2303.12246">Conformal Semantic Keypoint Detection with Statistical Guarantees</a>.
</p>
<div class="poster-carousel" id="carousel">
<div class="poster-item">
<img src="./assets/supp_examples/Neural Tangent Kernels for Axis-Aligned Tree Ensembles/gt.png" alt="gt poster">
<p class="caption-small">Generated by Author</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Neural Tangent Kernels for Axis-Aligned Tree Ensembles/4o_image.png" alt="GPT-4o Image">
<p class="caption-small">Generated by GPT-4o-image</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Neural Tangent Kernels for Axis-Aligned Tree Ensembles/4o_html.png" alt="GPT-4o Html">
<p class="caption-small">Generated by GPT-4o-html</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Neural Tangent Kernels for Axis-Aligned Tree Ensembles/ppt_agent.png" alt="PPT Agent">
<p class="caption-small">Generated by PPTAgent</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Neural Tangent Kernels for Axis-Aligned Tree Ensembles/owl.png" alt="OWL">
<p class="caption-small">Generated by OWL</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Neural Tangent Kernels for Axis-Aligned Tree Ensembles/ours.png" alt="PosterAgent">
<p class="caption-small">Generated by PostAgent</p>
</div>
</div>
<p class="caption-large">
Case-2: <a href="https://arxiv.org/pdf/2109.04983">Neural Tangent Kernels for Axis-Aligned Tree Ensembles</a>.
</p>
<!-- <div class="poster-carousel" id="carousel">
<div class="poster-item">
<img src="./assets/supp_examples/Sparse Parameterization for Epitomic Dataset Distillation/gt.png" alt="gt poster">
<p class="caption-small">Generated by Author</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Sparse Parameterization for Epitomic Dataset Distillation/4o_image.png" alt="GPT-4o Image">
<p class="caption-small">Generated by GPT-4o-image</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Sparse Parameterization for Epitomic Dataset Distillation/4o_html.png" alt="GPT-4o Html">
<p class="caption-small">Generated by GPT-4o-html</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Sparse Parameterization for Epitomic Dataset Distillation/ppt_agent.png" alt="PPT Agent">
<p class="caption-small">Generated by PPTAgent</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Sparse Parameterization for Epitomic Dataset Distillation/owl.png" alt="OWL">
<p class="caption-small">Generated by OWL</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Sparse Parameterization for Epitomic Dataset Distillation/ours.png" alt="PosterAgent">
<p class="caption-small">Generated by PostAgent</p>
</div>
</div>
<p class="caption-large">
Case-3: <a href="https://papers.nips.cc/paper_files/paper/2023/file/9e8889198d16fb79926e71adbe38cae4-Paper-Conference.pdf">Sparse Parameterization for Epitomic Dataset Distillation</a>.
</p> -->
<div class="poster-carousel" id="carousel">
<div class="poster-item">
<img src="./assets/supp_examples/Truly Scale-Equivariant Deep Nets with Fourier Layers/gt.png" alt="gt poster">
<p class="caption-small">Generated by Author</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Truly Scale-Equivariant Deep Nets with Fourier Layers/4o_image.png" alt="GPT-4o Image">
<p class="caption-small">Generated by GPT-4o-image</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Truly Scale-Equivariant Deep Nets with Fourier Layers/4o_html.png" alt="GPT-4o Html">
<p class="caption-small">Generated by GPT-4o-html</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Truly Scale-Equivariant Deep Nets with Fourier Layers/ppt_agent.png" alt="PPT Agent">
<p class="caption-small">Generated by PPTAgent</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Truly Scale-Equivariant Deep Nets with Fourier Layers/owl.png" alt="OWL">
<p class="caption-small">Generated by OWL</p>
</div>
<div class="poster-item">
<img src="./assets/supp_examples/Truly Scale-Equivariant Deep Nets with Fourier Layers/ours.png" alt="PosterAgent">
<p class="caption-small">Generated by PostAgent</p>
</div>
</div>
<p class="caption-large">
Case-3: <a href="https://arxiv.org/pdf/2311.02922">Truly Scale-Equivariant Deep Nets with Fourier Layers</a>.
</p>
</div>
</div>
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<section class="section" id="BibTeX">
<div class="container content is-max-desktop">
<h2 class="title">BibTeX</h2>
<pre><code>
@misc{pang2025paper2postermultimodalposterautomation,
title={Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers},
author={Wei Pang and Kevin Qinghong Lin and Xiangru Jian and Xi He and Philip Torr},
year={2025},
eprint={2505.21497},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2505.21497},
}
</code></pre>
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