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Neuroscience, Education and Cognitive Function

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Attention is All You Need Until You Need Retention
M. Murat Yaslioglu · 16 September 2026
Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this paper proposed a Retention Layer, a persistent memory that a Transformer block reads with attention and writes during use. Because most of what a deployed model c…
Intellectual Stewardship: Re-adapting Human Minds for Creative Knowledge Work in the Age of AI
Jianwei Zhang · 20 March 2026
Background: Amid the opportunities and risks introduced by generative AI, learning research needs to envision how human minds and responsibilities should re-adapt as AI continues to augment or automate various tasks. Approach: Drawing on theories of learning, intelligence, and knowledge creation, …
Neuro-Symbolic Imitation Learning: Discovering Symbolic Abstractions for Skill Learning
Leon Keller, Daniel Tanneberg, Jan Peters · 4 November 2025
Imitation learning is a popular method for teaching robots new behaviors. However, most existing methods focus on teaching short, isolated skills rather than long, multi-step tasks. To bridge this gap, imitation learning algorithms must not only learn individual skills but also an abstract understan…