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This paper introduces a data-free universal prior over syntactic structures from a cognitive model of language production, demonstrating it assigns higher probabilities to attested trees and correlates with language-specific data across 138 languages.
This paper investigates how humans communicate under strict vocabulary limitations, comparing their incremental production strategies to greedy and globally optimal sampling algorithms using Sequential Monte Carlo inference with large language models.