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DTSTART;TZID=America/Los_Angeles:20220401T110000
DTEND;TZID=America/Los_Angeles:20220401T130000
DTSTAMP:20220328T213936Z
CREATED:20210818T174443Z
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UID:31694-1648810800-1648818000@linguistics.ucla.edu
SUMMARY:Bob Frank (Yale) - computational\, syntax
DESCRIPTION:Linguistic Productivity in Neural Networks: Representation and Inductive BiasA fundamental fact about human language is its productivity: speakers are able to understand and produce forms different from those that they have previously encountered. Linguists typically account for this fact by positing abstract grammars that characterize structural representations for an infinity of possible forms. At the same time\, recent neural network models have achieved extraordinary levels of performance on practical NLP tasks without any explicit abstract grammar or structured representations. This remarkable success raises the question of whether these models do in fact exhibit productivity of the sort human speakers are capable of\, even in the absence of abstract grammar. In this talk\, I will explore this question from two perspectives. First\, I will discuss a line of work that investigates this question in the context of large pre-trained language models that have been at the forefront of contemporary NLP.  We ask whether these models show evidence of productive knowledge of selectional restrictions that cut across variation in syntactic context (deriving from argument structure alternations like dative shift or syntactic “transformations” like passivization). For the second part of the talk\, I will drill down to the properties of the neural network models themselves\, and consider what kinds of biases they exhibit when they learn: how do they perform in the face of ambiguous data\, and how do their biases differ from human generalization? To conclude\, I will consider the viability of different approaches to fostering linguistic abstraction in these models\,  by modifying the structure of model itself or the way in which training takes place.
URL:https://linguistics.ucla.edu/event/bob-frank-yale-computational-syntax/
LOCATION:Haines 118
CATEGORIES:Colloquium
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DTSTART;TZID=America/Los_Angeles:20220401T110000
DTEND;TZID=America/Los_Angeles:20220401T130000
DTSTAMP:20220331T213105Z
CREATED:20220328T212535Z
LAST-MODIFIED:20220331T213105Z
UID:35663-1648810800-1648818000@linguistics.ucla.edu
SUMMARY:Colloquium Speaker-Bob Frank (Yale)
DESCRIPTION:computational\, syntax
URL:https://linguistics.ucla.edu/event/colloquium-speaker-bob-frank-yale/
LOCATION:Haines 118
CATEGORIES:Colloquium
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220408T121500
DTEND;TZID=America/Los_Angeles:20220408T130000
DTSTAMP:20220408T171641Z
CREATED:20220404T151830Z
LAST-MODIFIED:20220408T171641Z
UID:35779-1649420100-1649422800@linguistics.ucla.edu
SUMMARY:Colloquium Nominee's Minority Status
DESCRIPTION:
URL:https://linguistics.ucla.edu/event/colloquium-nominees-minority-status/
CATEGORIES:Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220422T110000
DTEND;TZID=America/Los_Angeles:20220422T140000
DTSTAMP:20220422T175408Z
CREATED:20220122T141559Z
LAST-MODIFIED:20220422T175408Z
UID:34831-1650625200-1650636000@linguistics.ucla.edu
SUMMARY:Lisa Davidson (NYU) - phonetics
DESCRIPTION:
URL:https://linguistics.ucla.edu/event/lisa-davidson-nyu-phonetics-2/
LOCATION:Haines 118
CATEGORIES:Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220429T110000
DTEND;TZID=America/Los_Angeles:20220429T130000
DTSTAMP:20220428T210112Z
CREATED:20220404T170337Z
LAST-MODIFIED:20220428T210112Z
UID:35792-1651230000-1651237200@linguistics.ucla.edu
SUMMARY:Maura O'Leary's student colloquium talk- It's About Time: A long-expected relationship between nouns and tense
DESCRIPTION:It’s About Time: A long-expected relationship between nouns and tenseMaura O’Leary (UCLA) \nIt has been well established that the property times of verbs\, adjectives\, adverbs\, prepositional phrases\, participle phrases\, and relative clauses are all interpreted relative to the time argument introduced by the nearest scoping lambda abstractor (e.g.\, Abusch 1988\, Percus 2000\, Ogihara 2003\, Keshet 2008) – generally meaning that these property times overlap the reference time defined by sentential tense. However\, nominal property times have eluded such a clear-cut distribution; it seems that they need not overlap the tense’s reference time\, nor even the utterance time – leading some to conclude that nouns\, unlike all other predicates\, are altogether unaffected by tense (e.g.\, Enç 1981\, 1986; Musan 1995\, 1999; Tonhauser 2002\, 2006\, 2020). In this talk\, I show that the property times of nouns actually are defined relative to the time argument introduced by the nearest scoping lambda abstractor\, arguing that this fact has been obscured over the years by the existence of two nominal lexical aspectual classes\, which each derive their property time from their time argument in a unique way. With this confound accounted for\, I propose a single locality constraint which accounts for the binding of the time arguments of all predicate types. (This content\, which is only meant to account for predicates introducing novel referents\, comprises 2/3 of my dissertation – the remaining 1/3 accounts for the property times of nouns used in longer discourses to refer to familiar referents.)
URL:https://linguistics.ucla.edu/event/maura-olearys-student-colloquium-talk/
LOCATION:Haines 118
CATEGORIES:Colloquium
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