Martin Hebart

martinhebart.bsky.social

26 September 2026 05:59

What is the nature of universal representations in AI models, and what determines whether they emerge? Our paper accepted at #neurips2026 led by @florianmahner.bsky.social & @rothj.bsky.social addressed these questions comparing 162 vision models, with intriguing results. arxiv.org/abs/2605.13675 🧵

Michelle Greene

mgreenephd.bsky.social

26 September 2026 05:59

🚨New paper alert! 🚨 The visual system tunes itself to the statistics of its input. How do individual experiences differently tune vision? In this work, @bjbalas.bsky.social and I examined how one individual difference—height—changes the visual diet and how this affects perception. 1/

Dongyan Lin

dongyanl1n.bsky.social

27 June 2026 19:59

(1/n) Thrilled to share my first paper at Meta FAIR! "EgoBabyVLM: Benchmarking Cross-Modal Learning from Naturalistic Egocentric Video Data" 👶 Human infants learn language from sparse, noisy multimodal input. Today's VLMs can't. We built a benchmark + challenge to close that gap. 🧵

Martin Hebart

martinhebart.bsky.social

18 May 2026 13:50

I'm proud to say we are releasing LAION-fMRI, a densely sampled 7T fMRI dataset of natural images, with very broad stimulus sampling for testing countless hypotheses and for deeply exploring brain representations. The dataset is now available at laion-fmri.hebartlab.com What does LAION-fMRI offer? 🧵

Stanford Vision and Perception Neuroscience Lab

stanfordvpnl.bsky.social

15 May 2026 22:45

Be sure to check out our lab's presentations and posters at VSS!