Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions (2019 · 154 citations)
Progress in machine learning usually follows a fixed pattern: people choose a problem, and researchers build algorithms to solve it.
Quality-Diversity through AI Feedback (2023 · 19 citations)
Quality-diversity (QD) search maintains a population of solutions that are both good and varied. However, it has rarely been used for creative text because quality and diversity are hard to define in code. The authors propose QDAIF, an evolutionary method in which language models handle all three parts of QD search.…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

Designing neural networks through neuroevolution ↗Nature Machine Intelligence · no summary yetKenneth Owen Stanley et al.2018 · 702 citations
Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their SolutionsarXiv:1901.01753Rui Wang, Joel Lehman, Jeff Clune, et al.2019 · 154 citations
Quality-Diversity through AI FeedbackarXiv:2310.13032Herbie Bradley, Andrew Dai, Hannah Teufel, et al.2023 · 19 citations

Co-authors here

9 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 65 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated 3 November 2026