Jagrut Nemade

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs

Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse domains, but developing high-performing models for specialized applications often requires substantial human annotation — a process that is time-consuming, labor-intensive, and expensive. In this paper, we address