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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 101110 of 308 papers

TitleStatusHype
E-Gen: Leveraging E-Graphs to Improve Continuous Representations of Symbolic ExpressionsCode0
Enhancing Clinical Models with Pseudo Data for De-identificationCode0
Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classificationCode0
JABBERWOCK: A Tool for WebAssembly Dataset Generation and Its Application to Malicious Website DetectionCode0
Dataset Generation and Bonobo Classification from Weakly Labelled VideosCode0
Automating 3D Dataset Generation with Neural Radiance FieldsCode0
A Dataset Generation Toolbox for Dynamic Security Assessment: On the Role of the Security BoundaryCode0
Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling AutonomyCode0
Building Large Machine Reading-Comprehension Datasets using Paragraph VectorsCode0
JAPAGEN: Efficient Few/Zero-shot Learning via Japanese Training Dataset Generation with LLMCode0
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