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Transformer Mechanisms Mimic Frontostriatal Gating Operations When Trained on Human Working Memory Tasks
Models based on the Transformer neural network architecture have seen success on a wide variety of tasks that appear to require complex "cognitive branching" -- or the ability to maintain pursuit of one goal while accomplishing others.
Human Curriculum Effects Emerge with In-Context Learning in Neural Networks
Human learning is sensitive to rule-like structure and the curriculum of examples used for training.
Reward-Predictive Clustering
Recent advances in reinforcement-learning research have demonstrated impressive results in building algorithms that can out-perform humans in complex tasks.
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