Generating Benchmark Health Data Using a Tabular Diffusion Transformer
Cross-Tabular Data Generation (CTDG) seeks to learn a generative model from multiple heterogeneous tables and produce new synthetic tabular datasets. However, existing synthetic tabular data generation methods are largely restricted to single-input-table scenarios and struggle to effectively handle multiple heterogeneous tables with diverse feature sets. To address this limitation, we propose a two-stage framework for cross-tabular data generation. In the first stage, each heterogeneous raw table is transformed into a standardized statistical table with the same set of columns across all table
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- FuzzySimilar title/name (fuzzy) · 59%stabilityai/stable-diffusion-xl-base-1.0 →
“Fuzzy title match (0.73): “Generating Benchmark Health Data Using a Tabular Diffusion T” ≈ “stabilityai/stable-diffusion-xl-base-1.0””
- FuzzySimilar title/name (fuzzy) · 59%CompVis/stable-diffusion-v1-4 →
“Fuzzy title match (0.73): “Generating Benchmark Health Data Using a Tabular Diffusion T” ≈ “CompVis/stable-diffusion-v1-4””
- FuzzySimilar title/name (fuzzy) · 59%stabilityai/stable-diffusion-3.5-large →
“Fuzzy title match (0.73): “Generating Benchmark Health Data Using a Tabular Diffusion T” ≈ “stabilityai/stable-diffusion-3.5-large””
- FuzzyOverlapping authors or contributors · 62%modular/modular →
“Shared author/contributor keys: liu”
- FuzzyOverlapping authors or contributors · 62%Kong/kong →
“Shared author/contributor keys: kong”
- FuzzySimilar title/name (fuzzy) · 59%jeinlee1991/chinese-llm-benchmark →
“Fuzzy title match (0.73): “Generating Benchmark Health Data Using a Tabular Diffusion T” ≈ “jeinlee1991/chinese-llm-benchmark””
- LinkedLinked via arxiv author · 85%Zuhao Yang →
“Generating Benchmark Health Data Using a Tabular Diffusion Transformer”
- LinkedLinked via arxiv author · 85%Lisa Pilgram →
“Generating Benchmark Health Data Using a Tabular Diffusion Transformer”