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
Faithful Persona-based Conversational Dataset Generation with Large Language ModelsCode1
Global Tensor Motion PlanningCode1
DCFace: Synthetic Face Generation with Dual Condition Diffusion ModelCode1
Detecting Anti-Vaccine Users on TwitterCode1
CamDiff: Camouflage Image Augmentation via Diffusion ModelCode1
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language ModelsCode1
Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languagesCode1
Cephalo: Multi-Modal Vision-Language Models for Bio-Inspired Materials Analysis and DesignCode1
Forcing Diffuse Distributions out of Language ModelsCode1
Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic SegmentationCode1
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