ORiGAMi synthesizes sparse semi-structured mixed-type JSON data using path-encoded autoregressive tokenization and schema constraints, outperforming flattened tabular baselines on 17 of 18 fidelity, detection, and utility metrics while keeping privacy above 96%.
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DealMaTe proposes a simplified diffusion framework for material transfer that injects multi-dimensional 3D conditions via Multi-Dim 3D Shader LoRA and Shader Causal Mutual Attention with KV caching.
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Autoregressive Synthesis of Sparse and Semi-Structured Mixed-Type Data
ORiGAMi synthesizes sparse semi-structured mixed-type JSON data using path-encoded autoregressive tokenization and schema constraints, outperforming flattened tabular baselines on 17 of 18 fidelity, detection, and utility metrics while keeping privacy above 96%.
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DealMaTe: Multi-Dimensional Material Transfer via Diffusion Transformer
DealMaTe proposes a simplified diffusion framework for material transfer that injects multi-dimensional 3D conditions via Multi-Dim 3D Shader LoRA and Shader Causal Mutual Attention with KV caching.