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 110 of 308 papers

TitleStatusHype
Better Synthetic Data by Retrieving and Transforming Existing DatasetsCode7
Synthetic Dataset Generation for Adversarial Machine Learning ResearchCode6
AutoCoder: Enhancing Code Large Language Model with AIEV-InstructCode4
Prompt2Model: Generating Deployable Models from Natural Language InstructionsCode4
Hierarchical Lexical Graph for Enhanced Multi-Hop RetrievalCode3
RAGEval: Scenario Specific RAG Evaluation Dataset Generation FrameworkCode3
Vision Language Action Models in Robotic Manipulation: A Systematic ReviewCode2
CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation ModelsCode2
Physics Informed Distillation for Diffusion ModelsCode2
DataDream: Few-shot Guided Dataset GenerationCode2
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