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Found 5 papers, 2 papers with code
Large language models surpass human experts in predicting neuroscience results
LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts.
Understanding top-down attention using task-oriented ablation design
Then on each task we compare the performance of two neural networks, one with top-down attention and one without.
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance
Furthermore, an LCN's predictions can be used in a two-stage approach to encourage a high-capacity network (HCN) to rely on deeper invariant features that should generalize broadly.
The perceptual boost of visual attention is task-dependent in naturalistic settings
Is the resulting perceptual boost task-dependent in naturalistic settings?
The Costs and Benefits of Goal-Directed Attention in Deep Convolutional Neural Networks
Motivated by selective attention in categorisation models, we developed a goal-directed attention mechanism that can process naturalistic (photographic) stimuli.
