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Found 7 papers, 4 papers with code
MindSet: Vision. A toolbox for testing DNNs on key psychological experiments
Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision.
Visual Reasoning in Object-Centric Deep Neural Networks: A Comparative Cognition Approach
To this end, these models use several kinds of attention mechanisms to segregate the individual objects in a scene from the background and from other objects.
The role of object-centric representations, guided attention, and external memory on generalizing visual relations
Visual reasoning is a long-term goal of vision research.
Learning Relational Rules from Rewards
To demonstrate the potential of our approach, we build a simple model of relational policy learning based on a function approximator developed in RRL.
A Theory of Relation Learning and Cross-domain Generalization
People readily generalize knowledge to novel domains and stimuli.
The relational processing limits of classic and contemporary neural network models of language processing
In the present study we tested the Story Gestalt model (St. John, 1992), a classic PDP model of text comprehension, and a Sequence-to-Sequence with Attention model (Bahdanau et al., 2015), a contemporary deep learning architecture for text processing.
Human-like generalization in a machine through predicate learning
Humans readily generalize, applying prior knowledge to novel situations and stimuli.
