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Found 3 papers, 2 papers with code
On the generalization capacity of neural networks during generic multimodal reasoning
On the other hand, neither of these architectural features led to productive generalization, suggesting fundamental limitations of existing architectures for specific types of multimodal generalization.
Compositional generalization through abstract representations in human and artificial neural networks
Our findings give empirical support to the role of compositional generalization in human behavior, implicate abstract representations as its neural implementation, and illustrate that these representations can be embedded into ANNs by designing simple and efficient pretraining procedures.
Deep learning models for predicting RNA degradation via dual crowdsourcing
Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504-1588 nucleotides) with improved accuracy compared to previously published models.
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