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 6170 of 308 papers

TitleStatusHype
Chip Placement with Diffusion ModelsCode1
Image Generation for Efficient Neural Network Training in Autonomous Drone RacingCode1
DiffuGen: Adaptable Approach for Generating Labeled Image Datasets using Stable Diffusion ModelsCode1
Learning-based NLOS Detection and Uncertainty Prediction of GNSS Observations with Transformer-Enhanced LSTM NetworkCode1
LIQUID: A Framework for List Question Answering Dataset GenerationCode1
MORSE-500: A Programmatically Controllable Video Benchmark to Stress-Test Multimodal ReasoningCode1
Sim-Suction: Learning a Suction Grasp Policy for Cluttered Environments Using a Synthetic BenchmarkCode1
Actionet: An Interactive End-To-End Platform For Task-Based Data Collection And Augmentation In 3D EnvironmentCode1
CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and AugmentationCode1
ZeroGen: Efficient Zero-shot Learning via Dataset GenerationCode1
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