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Found 12 papers, 7 papers with code
Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI
They all have similar performance and they outperform transformers that are trained from scratch by a large margin.
Opening the Black Box: Analyzing Attention Weights and Hidden States in Pre-trained Language Models for Non-language Tasks
Investigating deep learning language models has always been a significant research area due to the ``black box" nature of most advanced models.
Grounding Psychological Shape Space in Convolutional Neural Networks
Shape information is crucial for human perception and cognition, and should therefore also play a role in cognitive AI systems.
Fast Concept Mapping: The Emergence of Human Abilities in Artificial Neural Networks when Learning Embodied and Self-Supervised
Following this, the representations learned through interaction with the world can be used to associate semantic concepts such as different types of doors.
Learning Semantically Meaningful Representations Through Embodiment
How do humans acquire a meaningful understanding of the world with little to no supervision or semantic labels provided by the environment?
Generalizing Psychological Similarity Spaces to Unseen Stimuli
The cognitive framework of conceptual spaces proposes to represent concepts as regions in psychological similarity spaces.
Formal Ways for Measuring Relations between Concepts in Conceptual Spaces
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge.
Formalized Conceptual Spaces with a Geometric Representation of Correlations
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge.
A Comprehensive Implementation of Conceptual Spaces
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge.
Measuring Relations Between Concepts In Conceptual Spaces
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge.
A Thorough Formalization of Conceptual Spaces
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge.
Towards Grounding Conceptual Spaces in Neural Representations
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge.
