mlsanityData to 14 Oct 2026

FigGen: Text to Scientific Figure Generation

arXiv 2306.00800 ↗First posted 1 Jun 2023cs.CV cs.AIcited by 17

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Abstract (arXiv)

The generative modeling landscape has experienced tremendous growth in recent years, particularly in generating natural images and art. Recent techniques have shown impressive potential in creating complex visual compositions while delivering impressive realism and quality. However, state-of-the-art methods have been focusing on the narrow domain of natural images, while other distributions remain unexplored. In this paper, we introduce the problem of text-to-figure generation, that is creating scientific figures of papers from text descriptions. We present FigGen, a diffusion-based approach for text-to-figure as well as the main challenges of the proposed task. Code and models are available at https://github.com/joanrod/figure-diffusion

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 19 of its 21 references that are in the map. First posted on arXiv 1 Jun 2023.

Builds on

19 of 21 references.

References · 19

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  5. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  6. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  7. 2020Denoising Diffusion Implicit Modelscited by 9,781
  8. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  9. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  10. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  11. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  12. 2022Classifier-Free Diffusion Guidancecited by 5,847
7 more
  1. 2022Generative Adversarial Networkscited by 5,627
  2. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  3. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
  4. 2021Alias-Free Generative Adversarial Networkscited by 1,184
  5. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 931
  6. 2022OCR-VQGAN: Taming Text-within-Image Generationcited by 31
  7. 2023Beyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Designcited by 23

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 0; 2025: 4; 2026: 10.

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  1. 2023StarVector: Generating Scalable Vector Graphics Code from Images and Textcited by 102
  2. 2023AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZcited by 79
  3. 2023Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformerscited by 36
  4. 2026PaperBanana: Automating Academic Illustration for AI Scientistscited by 26
  5. 2025TikZero: Zero-Shot Text-Guided Graphics Program Synthesiscited by 24
  6. 2025SVGen: Interpretable Vector Graphics Generation with Large Language Modelscited by 14
  7. 2026TikZilla: Scaling Text-to-TikZ with High-Quality Data and Reinforcement Learningcited by 7
  8. 2026Automatic Method Illustration Generation for AI Scientific Papers via Drawing Middleware Creation, Evolution, and Orchestrationcited by 5
  9. 2026VectorGym: A Multi-Task Benchmark for SVG Code Generation, Sketching and Editingcited by 5
  10. 2025SciGA: A Comprehensive Dataset for Designing Graphical Abstracts in Academic Paperscited by 2
  11. 2025TechImage-Bench: Rubric-Based Evaluation for Technical Image Generationcited by 2
  12. 2026GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Modelscited by 2
5 more
  1. 2026Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptionscited by 1
  2. 2026SciForma: Structure-Faithful Generation of Scientific Diagramscited by 1
  3. 2026GenGA: Editable and Data-Grounded Graphical Abstract Generation for Academic Paperscited by 0
  4. 2026Back2Struct: Making Structured Images Editable Againcited by 0
  5. 2026One Figure, Every Canvas: Editable Flowchart Relayout via Agentic Pipelinecited by 0