LLM-generated synthetic behavior data improves mobility and smartphone-use prediction models by up to 18.9% and captures roughly 60 to 88% of the gains from real-data fine-tuning.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Large language model as user daily behavior data generator: balancing population diversity and individual personality
LLM-generated synthetic behavior data improves mobility and smartphone-use prediction models by up to 18.9% and captures roughly 60 to 88% of the gains from real-data fine-tuning.