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
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMsCode1
Global Tensor Motion PlanningCode1
CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and AugmentationCode1
ColabSfM: Collaborative Structure-from-Motion by Point Cloud RegistrationCode1
DCFace: Synthetic Face Generation with Dual Condition Diffusion ModelCode1
Developing a Scalable Benchmark for Assessing Large Language Models in Knowledge Graph EngineeringCode1
Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languagesCode1
Automated Multi-level Preference for MLLMsCode1
Forcing Diffuse Distributions out of Language ModelsCode1
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language ModelsCode1
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