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 121130 of 308 papers

TitleStatusHype
Semantically Rich Local Dataset Generation for Explainable AI in GenomicsCode0
TheoremLlama: Transforming General-Purpose LLMs into Lean4 ExpertsCode1
Channel Modeling Aided Dataset Generation for AI-Enabled CSI Feedback: Advances, Challenges, and Solutions0
UniGen: A Unified Framework for Textual Dataset Generation Using Large Language ModelsCode2
DataFreeShield: Defending Adversarial Attacks without Training Data0
SEC-QA: A Systematic Evaluation Corpus for Financial QA0
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in ExplanationsCode0
Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels0
Federated Learning-based Collaborative Wideband Spectrum Sensing and Scheduling for UAVs in UTM Systems0
Cephalo: Multi-Modal Vision-Language Models for Bio-Inspired Materials Analysis and DesignCode1
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