7 citations · 13 across the 3 of their papers we have counts for
3 papers
cs.CV2025★ 1 cited
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…
cs.CL2023★ 7 cited
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…
cs.AI2023★ 5 cited
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization
Li Ding, Jenny Zhang, Jeff Clune +2
Reinforcement Learning from Human Feedback (RLHF) has shown potential in qualitative tasks where easily defined performance measures are lacking. However, there are drawbacks when…