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 5160 of 308 papers

TitleStatusHype
Holistic Audit Dataset Generation for LLM Unlearning via Knowledge Graph Traversal and Redundancy Removal0
SpecDM: Hyperspectral Dataset Synthesis with Pixel-level Semantic Annotations0
Beyond Translation: LLM-Based Data Generation for Multilingual Fact-CheckingCode0
Synth It Like KITTI: Synthetic Data Generation for Object Detection in Driving ScenariosCode0
TreeCut: A Synthetic Unanswerable Math Word Problem Dataset for LLM Hallucination EvaluationCode0
One-Shot Federated Learning with Classifier-Free Diffusion Models0
MultiFloodSynth: Multi-Annotated Flood Synthetic Dataset Generation0
Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning0
Synthetic User Behavior Sequence Generation with Large Language Models for Smart Homes0
iTRI-QA: a Toolset for Customized Question-Answer Dataset Generation Using Language Models for Enhanced Scientific Research0
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