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Found 10 papers, 7 papers with code
Auxiliary task demands mask the capabilities of smaller language models
Developmental psychologists have argued about when cognitive capacities such as language understanding or theory of mind emerge.
Learning the meanings of function words from grounded language using a visual question answering model
Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning, as well as early evidence that they are sensitive to alternative expressions when interpreting language.
The Emergence of the Shape Bias Results from Communicative Efficiency
By the age of two, children tend to assume that new word categories are based on objects' shape, rather than their color or texture; this assumption is called the shape bias.
From partners to populations: A hierarchical Bayesian account of coordination and convention
Languages are powerful solutions to coordination problems: they provide stable, shared expectations about how the words we say correspond to the beliefs and intentions in our heads.
Relational reasoning and generalization using non-symbolic neural networks
In the two latter cases, our models perform tasks proposed in previous work to demarcate human-unique symbolic abilities.
Characterizing the dynamics of learning in repeated reference games
The language we use over the course of conversation changes as we establish common ground and learn what our partner finds meaningful.
Pedagogical learning
samples are, in a sense, uninformative---they produce data without regard to how good this data is for learning.
Prosodic Features from Large Corpora of Child-Directed Speech as Predictors of the Age of Acquisition of Words
The impressive ability of children to acquire language is a widely studied phenomenon, and the factors influencing the pace and patterns of word learning remains a subject of active research.
Parsing entire discourses as very long strings: Capturing topic continuity in grounded language learning
Grounded language learning, the task of mapping from natural language to a representation of meaning, has attracted more and more interest in recent years.
