3 papers
cs.AI2026
In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models
Sam Earle, Kai Arulkumaran, Andrew Dai +3
We are in the midst of large-scale industrial and academic efforts to automate the processes of scientific, technological and creative production through AI-driven assistants. Hist…
cs.LG2024
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.IR2024
Improving Vietnamese Legal Document Retrieval using Synthetic Data
Son Pham Tien, Hieu Nguyen Doan, An Nguyen Dai +1
In the field of legal information retrieval, effective embedding-based models are essential for accurate question-answering systems. However, the scarcity of large annotated datase…