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Found 6 papers, 1 papers with code
Cultural evolution via iterated learning and communication explains efficient color naming systems
It has been argued that semantic systems reflect pressure for efficiency, and a current debate concerns the cultural evolutionary process that produces this pattern.
Does BERT agree? Evaluating knowledge of structure dependence through agreement relations
Learning representations that accurately model semantics is an important goal of natural language processing research.
Semantic categories of artifacts and animals reflect efficient coding
Recently, this idea has been cast in terms of a general information-theoretic principle of efficiency, the Information Bottleneck (IB) principle, and it has been shown that this principle accounts for the emergence and evolution of named color categories across languages, including soft structure and patterns of inconsistent naming.
Probing sentence embeddings for structure-dependent tense
Learning universal sentence representations which accurately model sentential semantic content is a current goal of natural language processing research.
Efficient human-like semantic representations via the Information Bottleneck principle
This work thus identifies a computational principle that characterizes human semantic systems, and that could usefully inform semantic representations in machines.
Color naming reflects both perceptual structure and communicative need
We show that greater communicative precision for warm than for cool colors, and greater communicative need, may both be explained by perceptual structure.
