4 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 4 cited
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models
Alex Havrilla, Andrew Dai, Laura O'Mahony +17
Synthetic data generation with Large Language Models is a promising paradigm for augmenting natural data over a nearly infinite range of tasks. Given this variety, direct compariso…
cs.LG2024★ 3 cited
Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought
Alex Havrilla, Maia Iyer
During both pretraining and fine-tuning, Large Language Models (\textbf{LLMs}) are trained on trillions of tokens of text of widely varying quality. Both phases of training typical…