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 91100 of 308 papers

TitleStatusHype
IrrMap: A Large-Scale Comprehensive Dataset for Irrigation Method MappingCode0
Guidance for Intra-cardiac Echocardiography Manipulation to Maintain Continuous Therapy Device Tip Visibility0
Estimating Commonsense Scene Composition on Belief Scene Graphs0
Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments0
TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language ModelsCode0
V^2R-Bench: Holistically Evaluating LVLM Robustness to Fundamental Visual Variations0
MirrorVerse: Pushing Diffusion Models to Realistically Reflect the World0
Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering0
Geometric Generality of Transformer-Based Gröbner Basis ComputationCode0
DeepWheel: Generating a 3D Synthetic Wheel Dataset for Design and Performance Evaluation0
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