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 201210 of 308 papers

TitleStatusHype
JABBERWOCK: A Tool for WebAssembly Dataset Generation and Its Application to Malicious Website DetectionCode0
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning BenchmarksCode0
Sim-Suction: Learning a Suction Grasp Policy for Cluttered Environments Using a Synthetic BenchmarkCode1
Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic TasksCode1
Sim-MEES: Modular End-Effector System Grasping Dataset for Mobile Manipulators in Cluttered EnvironmentsCode0
Diffusion Dataset Generation: Towards Closing the Sim2Real Gap for Pedestrian Detection0
Zero-shot racially balanced dataset generation using an existing biased StyleGAN2Code0
Benchmark dataset and instance generator for Real-World Three-Dimensional Bin Packing Problems0
PAXQA: Generating Cross-lingual Question Answering Examples at Training ScaleCode0
Synthetic Datasets for Autonomous Driving: A Survey0
Show:102550
← PrevPage 21 of 31Next →

No leaderboard results yet.