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 211220 of 308 papers

TitleStatusHype
Automated dataset generation for image recognition using the example of taxonomy0
AutoHall: Automated Hallucination Dataset Generation for Large Language Models0
Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels0
Pseudo Dataset Generation for Out-of-Domain Multi-Camera View Recommendation0
A systematic dataset generation technique applied to data-driven automotive aerodynamics0
Radar Artifact Labeling Framework (RALF): Method for Plausible Radar Detections in Datasets0
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture0
RainSD: Rain Style Diversification Module for Image Synthesis Enhancement using Feature-Level Style Distribution0
A Seed-Augment-Train Framework for Universal Digit Classification0
Realistic Surgical Image Dataset Generation Based On 3D Gaussian Splatting0
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