LiFT Framework Enhances Longitudinal NLP Tasks with Instruction Fine-Tuning
Researchers introduced LiFT, a framework that improves large language models' ability to handle longitudinal NLP tasks. The method uses instruction fine-tuning to better track temporal changes in human behavior and opinions.