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X-WR-CALDESC:Events for ILCB
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DTSTART;TZID=Europe/Paris:20211105T160000
DTEND;TZID=Europe/Paris:20211105T170000
DTSTAMP:20260422T113946
CREATED:20211002T073439Z
LAST-MODIFIED:20211018T094731Z
UID:13462-1636128000-1636131600@www.ilcb.fr
SUMMARY:CoCoDev
DESCRIPTION:Production practice is more effective than comprehension for second language learning\n  Elise Hopman  (University of Wisconsin-Madison) \nAbstract: \nWhereas most classroom-based language instruction traditionally emphasizes comprehension-based learning\, memory research suggests that language production activities may provide a stronger learning experience than comprehension practice\, due to the meaningfully different task demands involved in producing versus comprehending language. Using both artificial and natural language learning experiments with adults\, I show that production exercises are more effective than comprehension exercises for learning the vocabulary and grammar of a foreign language. I will discuss these findings in the broader context of research implying that production and production-like activities might play a privileged role during learning more generally. \n 
URL:https://www.ilcb.fr/event/production-practice-is-more-effective-than-comprehension-for-second-language-learning/
LOCATION:via zoom
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20211112T160000
DTEND;TZID=Europe/Paris:20211112T170000
DTSTAMP:20260422T113946
CREATED:20211002T073730Z
LAST-MODIFIED:20211018T094923Z
UID:13464-1636732800-1636736400@www.ilcb.fr
SUMMARY:CoCoDev
DESCRIPTION:BabyBERTa: Learning More Grammar With Small-Scale Child-Directed Language\n  Philip Huebner  (University of Illinos\, Urbana-Champaign) \nAbstract: \nTransformer-based language models have taken the NLP world by storm. However\, their potential for addressing important questions in language acquisition research has been largely ignored. In this work\, we examined the grammatical knowledge of RoBERTa (Liu et al.\, 2019) when trained on a 5M word corpus of language acquisition data to simulate the input available to children between the ages 1 and 6. Using the behavioral probing paradigm\, we found that a smaller version of RoBERTa-base that never predicts unmasked tokens\, which we term BabyBERTa\, acquires grammatical knowledge comparable to that of pre-trained RoBERTa-base – and does so with approximately 15X fewer parameters and 6\,000X fewer words. We discuss implications for building more efficient models and the learnability of grammar from input available to children. Lastly\, to support research on this front\, we release our novel grammar test suite that is compatible with the small vocabulary of child-directed input. \n 
URL:https://www.ilcb.fr/event/babyberta-learning-more-grammar-with-small-scale-child-directed-language/
LOCATION:via zoom
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20211119T120000
DTEND;TZID=Europe/Paris:20211119T140000
DTSTAMP:20260422T113946
CREATED:20211002T074009Z
LAST-MODIFIED:20211116T090125Z
UID:13466-1637323200-1637330400@www.ilcb.fr
SUMMARY:Computational study of active and interactive word learning
DESCRIPTION:Lieke Gelderloos\, a Ph.D. researcher at Tilburg University\, whose work is at the intersection of cognitive science\, linguistics\, and artificial intelligence\n\n\nThe zoom link: https://univ-amu-fr.zoom.us/j/2515421853\n\n\n\nAbstract: Models of cross-situational word learning typically characterize the learner as a passive observer. However\, a language learning child can actively participate in verbal and non-verbal communication. We present a computational model that learns to map words to objects in images through word comprehension and production. The productive and receptive parts of the model can operate independently\, but can also feed into each other. This introspective quality enables the model to learn through self-supervision\, and also to estimate its own word knowledge\, select optimal input\, and thereby alter its own learning trajectory. The modular set-up is also suitable for testing effects of communicative feedback. In this talk\, I will cover our findings regarding active selection of input\, and present preliminary results on tests with communicative feedback.\n\n 
URL:https://www.ilcb.fr/event/tba-6/
LOCATION:via zoom
CATEGORIES:CoCoDev
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20211126T120000
DTEND;TZID=Europe/Paris:20211126T143000
DTSTAMP:20260422T113946
CREATED:20210908T160000Z
LAST-MODIFIED:20211108T155443Z
UID:12472-1637928000-1637937000@www.ilcb.fr
SUMMARY:Aurélie Bidet-Caulet
DESCRIPTION:How does the human brain resist auditory distraction? \nOne main challenge for the attentive brain is to resist distracting information. Auditory distraction can result from predictable irrelevant information (e.g. ongoing background noise) or from unexpected\, transient and salient distracting events (e.g. phone ring\, fire alarm…). Using intracranial EEG\, scalp EEG and MEG data combined with behavioral measures\, we have investigated brain activities in the time and frequency domains to characterize the brain mechanisms involved in shielding from distraction\, in the healthy\, developing (children and ageing data)\, or dysfunctional (stroke or migraine patients) brain. I will present a first set of data showing that distinct inhibitory and facilitatory mechanisms support selective attention to reduce the impact of an irrelevant sound stream. Then\, I will present data showing that the impact of an unexpected salient environmental sound results from a balance between top-down and bottom-up mechanisms of attention.
URL:https://www.ilcb.fr/event/aurelie-bidet-caulet/
LOCATION:FRUMAM\, 3 place Victor Hugo\, Marseille\, 13001\, France
CATEGORIES:Lunch Talks
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