Sascha Bongni

Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs

Recent efforts in fine-tuning language models often rely on automatic data selection, commonly using Nearest Neighbors retrieval from large datasets. However, we theoretically show that this approach tends to select redundant data, limiting its effectiveness or even hurting performance. To address t…