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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Grounding Word Learning Across Situations ... 43rd Annual Meeting of the Cognitive Science Society 2021; Beser, Deniz; Cecil, Joe; Freedman, Marjorie; Gabbard, Ryan; Lichtefeld, Jacob; Marcus, Mitch; Payne, Sarah; Yang, Charles. - : Underline Science Inc., 2021 Abstract: Word learning models are typically evaluated as the problem of observing words together with sets of atomic objects and learn-ing an alignment between them. We use ADAM, a Python software platform for modeling grounded language acquisition, to evaluate a particular word learning model, Pursuit (Stevens, Gleitman, Trueswell, & Yang, 2017),under more realistic learning conditions (see e.g. Gleitman and Trueswell (2020) for review). In particular, we manipulate the degree of referential ambiguity and the salience of attentional cues available to the learner, and we present extensions to Pursuit which address the challenges of non-atomic meanings and exploiting attentional cues. ... Keyword: Applied Linguistics; Cognitive Science; Computational Intelligence; Computational Linguistics; Psycholinguistics URL: https://underline.io/lecture/26752-grounding-word-learning-across-situations https://dx.doi.org/10.48448/eajk-nr76 BASE Hide details 2 Grounding Word Learning Across Situations ... 43rd Annual Meeting of the Cognitive Science Society 2021; Beser, Deniz; Cecil, Joe. - : Underline Science Inc., 2021 BASE Show details

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