{
  "id": "fsa-cdm",
  "title": "Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation",
  "authors": [
    {
      "given": "Guojin",
      "family": "Zhong"
    },
    {
      "given": "Jin",
      "family": "Yuan"
    },
    {
      "given": "Pan",
      "family": "Wang"
    },
    {
      "given": "Kailun",
      "family": "Yang"
    },
    {
      "given": "Weili",
      "family": "Guan"
    },
    {
      "given": "Zhiyong",
      "family": "Li"
    }
  ],
  "year": 2023,
  "venue": "ACM Multimedia 2023",
  "paper_url": "https://arxiv.org/abs/2308.01147",
  "pdf_url": "https://arxiv.org/pdf/2308.01147",
  "summary": "FSA-CDM 将细粒度跨模态序列对齐、上下文建模和对比增强的扩散目标结合，用于标记语言到图像生成。",
  "connection": "这项后续工作沿用 Deng、Kojima 和 Rush 提出的任务与四个数据集，研究对齐与对比反馈。",
  "bibtex_type": "inproceedings",
  "citation_key": "zhong2023contrastaugmented",
  "source_urls": [
    "https://arxiv.org/html/2308.01147v1"
  ],
  "arxiv_id": "2308.01147",
  "arxiv_first_posted": "2023-08-02",
  "updated_at": "2026-11-11",
  "description_language": "zh-Hans",
  "abstract_language": "en",
  "record_url": "https://yuntiandeng.com/research/zh/papers/fsa-cdm/"
}