The curious case of developmental BERTology: On sparsity, transfer learning, generalization and the brain
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Abstract (arXiv)
In this essay, we explore a point of intersection between deep learning and neuroscience, through the lens of large language models, transfer learning and network compression. Just like perceptual and cognitive neurophysiology has inspired effective deep neural network architectures which in turn make a useful model for understanding the brain, here we explore how biological neural development might inspire efficient and robust optimization procedures which in turn serve as a useful model for the maturation and aging of the brain.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 7 Jul 2020.
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