SOTAVerified

Dataset Generation

The task involves enhancing the training of target application (e.g. autonomous driving systems) by generating datasets of diverse and critical elements (e.g. traffic scenarios). Traditional methods rely on expensive and limited datasets, which often fail to capture rare but essential situations that can pose risks during testing.

Papers

Showing 2130 of 308 papers

TitleStatusHype
Forcing Diffuse Distributions out of Language ModelsCode1
Global Tensor Motion PlanningCode1
DCFace: Synthetic Face Generation with Dual Condition Diffusion ModelCode1
Detecting Anti-Vaccine Users on TwitterCode1
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMsCode1
Bounding Box-Guided Diffusion for Synthesizing Industrial Images and Segmentation MapCode1
Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languagesCode1
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language ModelsCode1
Chip Placement with Diffusion ModelsCode1
Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic SegmentationCode1
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