mlsanityData to 7 Oct 2026

GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation

arXiv 2407.14982 ↗First posted 20 Jul 2024cs.CV cs.AIcited by 3

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Abstract (arXiv)

Tuning the parameters and prompts for improving AI-based text-to-image generation has remained a substantial yet unaddressed challenge. Hence we introduce GreenStableYolo, which improves the parameters and prompts for Stable Diffusion to both reduce GPU inference time and increase image generation quality using NSGA-II and Yolo. Our experiments show that despite a relatively slight trade-off (18%) in image quality compared to StableYolo (which only considers image quality), GreenStableYolo achieves a substantial reduction in inference time (266% less) and a 526% higher hypervolume, thereby advancing the state-of-the-art for text-to-image generation.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 9 of its 20 references that are in the map. First posted on arXiv 20 Jul 2024.

Builds on

9 of 20 references.

References · 9

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  3. 2016Generative Adversarial Text to Image Synthesiscited by 735
  4. 2023A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPTcited by 221
  5. 2021Pretrained Language Models for Text Generation: A Surveycited by 95
  6. 2023Full Stack Optimization of Transformer Inference: a Surveycited by 79
  7. 2024VideoStudio: Generating Consistent-Content and Multi-Scene Videoscited by 62
  8. 2022Large-scale Text-to-Image Generation Models for Visual Artists' Creative Workscited by 60
  9. 2019Genetic Algorithms for the Optimization of Diffusion Parameters in Content-Based Image Retrievalcited by 2

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Biascited by 2
  2. 2025Search-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmapcited by 0
  3. 2025SustainDiffusion: Optimising the Social and Environmental Sustainability of Stable Diffusion Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis
  2. 2025ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation
  3. 2024CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion
  4. 2023Emage: Non-Autoregressive Text-to-Image Generation
  5. 2025Hawk: Leveraging Spatial Context for Faster Autoregressive Text-to-Image Generation
  6. 2024AGFSync: Leveraging AI-Generated Feedback for Preference Optimization in Text-to-Image Generation
  7. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths
  8. 2025Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection