Genetic Prompt uses LLMs to run semantic-level crossover and mutation on text attributes from two far-apart parent examples, producing synthetic data that improves downstream NLP performance, especially for rare classes.
Output : B.6.8 MeQSum You need to generate synthetic data for the medical question summarization task
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Attributes as Textual Genes: Leveraging LLMs as Genetic Algorithm Simulators for Conditional Synthetic Data Generation
Genetic Prompt uses LLMs to run semantic-level crossover and mutation on text attributes from two far-apart parent examples, producing synthetic data that improves downstream NLP performance, especially for rare classes.