7 citations · 10 across the 4 of their papers we have counts for
4 papers
Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis
Akarsh Kumar, Jeff Clune, Joel Lehman +1
Much of the excitement in modern AI is driven by the observation that scaling up existing systems leads to better performance. But does better performance necessarily imply better…
Evolution and The Knightian Blindspot of Machine Learning
Joel Lehman, Elliot Meyerson, Tarek El-Gaaly +2
This paper claims that machine learning (ML) largely overlooks an important facet of general intelligence: robustness to a qualitatively unknown future in an open world. Such robus…
Automating the Search for Artificial Life with Foundation Models
Akarsh Kumar, Chris Lu, Louis Kirsch +4
With the recent Nobel Prize awarded for radical advances in protein discovery, foundation models (FMs) for exploring large combinatorial spaces promise to revolutionize many scient…
Quality-Diversity through AI Feedback
Herbie Bradley, Andrew Dai, Hannah Teufel +7
In many text-generation problems, users may prefer not only a single response, but a diverse range of high-quality outputs from which to choose. Quality-diversity (QD) search algor…