{
  "title": "Research notes",
  "updated": "2026-11-11",
  "home": "https://yuntiandeng.com/research/zh/",
  "bibliography": "https://yuntiandeng.com/research/zh/papers/",
  "downloads": "https://yuntiandeng.com/research/zh/data/",
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      "title": "大语言模型决策树：从 Tree Prompting 到智能体分类",
      "url": "https://yuntiandeng.com/research/zh/llm-decision-trees/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/llm-decision-trees.md",
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      "url": "https://yuntiandeng.com/research/zh/energy-based-text-generation/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/energy-based-text-generation.md",
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        "residual-ebm-jmlr"
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    {
      "title": "结构化解码：高阶 CRF、扩散语言模型与候选格",
      "url": "https://yuntiandeng.com/research/zh/structured-decoding/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/structured-decoding.md",
      "original_papers": [
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        "lattice2021"
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      "title": "把注意力建模为隐变量：学习注意力的概率分布",
      "url": "https://yuntiandeng.com/research/zh/probabilistic-attention/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/probabilistic-attention.md",
      "original_papers": [
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      "title": "如何评估长文本的结构",
      "url": "https://yuntiandeng.com/research/zh/long-form-evaluation/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/long-form-evaluation.md",
      "original_papers": [
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      "title": "学习渲染 LaTeX、SMILES、HTML 与乐谱",
      "url": "https://yuntiandeng.com/research/zh/learned-rendering/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/learned-rendering.md",
      "original_papers": [
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    {
      "title": "让人和 AI 智能体控制正在运行的训练任务",
      "url": "https://yuntiandeng.com/research/zh/interactive-training/",
      "markdown": "https://yuntiandeng.com/research/zh/data/guides/interactive-training.md",
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      "title": "Tree Prompting: Efficient Task Adaptation without Fine-Tuning",
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      "source": "https://arxiv.org/html/2310.14034v1",
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      "title": "Augmenting interpretable models with large language models during training",
      "record": "https://yuntiandeng.com/research/zh/papers/aug-tree/",
      "source": "https://www.nature.com/articles/s41467-023-43713-1",
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      "id": "gptree",
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      "record": "https://yuntiandeng.com/research/zh/papers/gptree/",
      "source": "https://arxiv.org/html/2411.08257v1",
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      "id": "act",
      "title": "ACT: Agentic Classification Tree",
      "record": "https://yuntiandeng.com/research/zh/papers/act/",
      "source": "https://arxiv.org/html/2509.26433v4",
      "json": "https://yuntiandeng.com/research/zh/data/papers/act.json",
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      "csl": "https://yuntiandeng.com/research/zh/data/papers/act.csl.json"
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      "id": "residual-ebm",
      "title": "Residual Energy-Based Models for Text Generation",
      "record": "https://yuntiandeng.com/research/zh/papers/residual-ebm/",
      "source": "https://arxiv.org/html/2004.11714v1",
      "json": "https://yuntiandeng.com/research/zh/data/papers/residual-ebm.json",
      "bibtex": "https://yuntiandeng.com/research/zh/data/papers/residual-ebm.bib",
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      "title": "Residual Energy-Based Models for Text",
      "record": "https://yuntiandeng.com/research/zh/papers/residual-ebm-jmlr/",
      "source": "https://www.jmlr.org/papers/v22/20-326.html",
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      "record": "https://yuntiandeng.com/research/zh/papers/edlm/",
      "source": "https://arxiv.org/html/2410.21357v4",
      "json": "https://yuntiandeng.com/research/zh/data/papers/edlm.json",
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      "title": "Unified Energy for Invariant and Independent Decoding in Diffusion Language Models",
      "record": "https://yuntiandeng.com/research/zh/papers/unified-energy/",
      "source": "https://arxiv.org/html/2606.09159v1",
      "json": "https://yuntiandeng.com/research/zh/data/papers/unified-energy.json",
      "bibtex": "https://yuntiandeng.com/research/zh/data/papers/unified-energy.bib",
      "csl": "https://yuntiandeng.com/research/zh/data/papers/unified-energy.csl.json"
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      "id": "neural-trf-nce",
      "title": "Learning Neural Trans-Dimensional Random Field Language Models with Noise-Contrastive Estimation",
      "record": "https://yuntiandeng.com/research/zh/papers/neural-trf-nce/",
      "source": "https://arxiv.org/abs/1710.10739",
      "json": "https://yuntiandeng.com/research/zh/data/papers/neural-trf-nce.json",
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      "csl": "https://yuntiandeng.com/research/zh/data/papers/neural-trf-nce.csl.json"
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      "id": "cascaded2020",
      "title": "Cascaded Text Generation with Markov Transformers",
      "record": "https://yuntiandeng.com/research/zh/papers/cascaded2020/",
      "source": "https://arxiv.org/abs/2006.01112",
      "json": "https://yuntiandeng.com/research/zh/data/papers/cascaded2020.json",
      "bibtex": "https://yuntiandeng.com/research/zh/data/papers/cascaded2020.bib",
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      "id": "lattice2021",
      "title": "Sequence-to-Lattice Models for Fast Translation",
      "record": "https://yuntiandeng.com/research/zh/papers/lattice2021/",
      "source": "https://aclanthology.org/2021.findings-emnlp.318/",
      "json": "https://yuntiandeng.com/research/zh/data/papers/lattice2021.json",
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      "id": "sun2019",
      "title": "Fast Structured Decoding for Sequence Models",
      "record": "https://yuntiandeng.com/research/zh/papers/sun2019/",
      "source": "https://proceedings.neurips.cc/paper_files/paper/2019/hash/74563ba21a90da13dacf2a73e3ddefa7-Abstract.html",
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      "id": "codd2026",
      "title": "Breaking the Factorization Barrier in Diffusion Language Models",
      "record": "https://yuntiandeng.com/research/zh/papers/codd2026/",
      "source": "https://proceedings.mlr.press/v306/li26fd.html",
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      "id": "dadlm2026",
      "title": "DA-DLM: Explicitly Modeling Token Dependencies in Diffusion Language Models",
      "record": "https://yuntiandeng.com/research/zh/papers/dadlm2026/",
      "source": "https://aclanthology.org/2026.emnlp-main.2094/",
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      "id": "lilicorr2026",
      "title": "LiLiCorr: Lightweight Likelihood Correlation of Parallel Drafts for Speculative Decoding",
      "record": "https://yuntiandeng.com/research/zh/papers/lilicorr2026/",
      "source": "https://arxiv.org/abs/2608.20530",
      "json": "https://yuntiandeng.com/research/zh/data/papers/lilicorr2026.json",
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      "id": "diffuspec2026",
      "title": "DiffuSpec: Unlocking Diffusion Language Models for Speculative Decoding",
      "record": "https://yuntiandeng.com/research/zh/papers/diffuspec2026/",
      "source": "https://aclanthology.org/2026.findings-acl.1048/",
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      "id": "latentattention2018",
      "title": "Latent Alignment and Variational Attention",
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      "source": "https://arxiv.org/abs/1807.03756",
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      "title": "Show, Attend and Tell: Neural Image Caption Generation with Visual Attention",
      "record": "https://yuntiandeng.com/research/zh/papers/showattendtell2015/",
      "source": "https://proceedings.mlr.press/v37/xuc15.html",
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      "source": "https://arxiv.org/abs/1702.00887",
      "json": "https://yuntiandeng.com/research/zh/data/papers/structuredattention2017.json",
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      "source": "https://aclanthology.org/C18-1142/",
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      "id": "bayesianattention2020",
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      "record": "https://yuntiandeng.com/research/zh/papers/bayesianattention2020/",
      "source": "https://arxiv.org/abs/2010.10604",
      "json": "https://yuntiandeng.com/research/zh/data/papers/bayesianattention2020.json",
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      "id": "model-criticism",
      "title": "Model Criticism for Long-Form Text Generation",
      "record": "https://yuntiandeng.com/research/zh/papers/model-criticism/",
      "source": "https://aclanthology.org/2022.emnlp-main.815/",
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      "source": "https://aclanthology.org/2021.acl-long.500/",
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      "source": "https://arxiv.org/abs/2210.05147",
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      "source": "https://arxiv.org/abs/2308.01147",
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      "source": "https://arxiv.org/abs/2607.18314",
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