🥳 I am incredibly humbled and grateful to share that our work, "Aligning machine and human visual representations across abstraction levels," has been published today in @nature.com ⬇️

Andrew Lampinen@lampinen.bsky.social · 9mo ago

What aspects of human knowledge do vision models like CLIP fail to capture, and how can we improve them? We suggest models miss key global organization; aligning them makes them more robust. Check out LukasMuttenthaler's work, finally out (in Nature!?) www.nature.com/articles/s41... + our blog! 1/3

No two humans behave exactly alike. But what about neural networks? We found early evidence that human-like individual differences in behavior emerge from networks trained with different initializations. Here’s a peek at our results—to be presented at UniReps & DBM @NeurIPS. Full paper on the way!

Human-like individual differences emerge from random weight initializations in neural networks

Much of AI research targets the behavior of an average human, a focus that traces to Turing's imitation game. Yet, no two human individuals behave exactly alike. In this study, we show that artificial...

biorxiv.org

Presenting our #NeurIPS2025 work on model–behavior alignment today. Could we even recognize the “right” model of behavior under flexible evaluation? Come chat about DNNs & human visual preception! Hall C-E #2010 Friday (today!) 4:30 – 7:30 PM neurips.cc/virtual/2025...

Excited to share my first paper: Model–Behavior Alignment under Flexible Evaluation: When the Best-Fitting Model Isn’t the Right One (NeurIPS 2025). link below.