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 101110 of 308 papers

TitleStatusHype
CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and AugmentationCode1
DiffAge3D: Diffusion-based 3D-aware Face Aging0
PADetBench: Towards Benchmarking Physical Attacks against Object DetectionCode1
CyberPal.AI: Empowering LLMs with Expert-Driven Cybersecurity Instructions0
Fire Dynamic Vision: Image Segmentation and Tracking for Multi-Scale Fire and Plume BehaviorCode0
The Fellowship of the LLMs: Multi-Agent Workflows for Synthetic Preference Optimization Dataset GenerationCode0
A systematic dataset generation technique applied to data-driven automotive aerodynamics0
Neural Network Surrogate and Projected Gradient Descent for Fast and Reliable Finite Element Model Calibration: a Case Study on an Intervertebral DiscCode0
Full-range Head Pose Geometric Data Augmentations0
RAGEval: Scenario Specific RAG Evaluation Dataset Generation FrameworkCode3
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