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
Measuring and Mitigating Hallucinations in Vision-Language Dataset Generation for Remote Sensing0
E-Gen: Leveraging E-Graphs to Improve Continuous Representations of Symbolic ExpressionsCode0
A Dataset Generation Toolbox for Dynamic Security Assessment: On the Role of the Security BoundaryCode0
The Invisible Hand: Unveiling Provider Bias in Large Language Models for Code Generation0
CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation ModelsCode2
Neural Error Covariance Estimation for Precise LiDAR Localization0
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language ModelsCode1
DynScene: Scalable Generation of Dynamic Robotic Manipulation Scenes for Embodied AI0
Low-Biased General Annotated Dataset Generation0
ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content ModerationCode1
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