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Found 5 papers, 0 papers with code
Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning
Cobweb, a human like category learning system, differs from other incremental categorization models in constructing hierarchically organized cognitive tree-like structures using the category utility measure.
Catastrophic Interference is Mitigated in Naturalistic Power-Law Learning Environments
In addition, because our method is orthogonal to other methods, future research can combine training in power-law environments with other continual learning mechanisms.
Neural Network Models of Becoming a Cardinal Principle Knower
As children enter elementary school, their understanding of the ordinal structure of numbers transitions from a memorized count list of the first 50-100 numbers to knowing the successor function and understanding the countably infinite.
Pre-training LLMs using human-like development data corpus
Pre-trained Large Language Models (LLMs) have shown success in a diverse set of language inference and understanding tasks.
Human Behavioral Benchmarking: Numeric Magnitude Comparison Effects in Large Language Models
This research shows the utility of understanding LLMs using behavioral benchmarks and points the way to future work on the number representations of LLMs and their cognitive plausibility.
