Sentence and Discourse Processing (PSYC 5583)
Fall, 2023 (timeslot to be determined)
Instructor: Whitney Tabor (email@example.com)
This course provides an introduction to psycho- and computational linguistics at the sentence and discourse levels. It includes a theoretically-grounded exploration of Deep Learning/Large Language Models (LLMs), linking these to psycholinguistic work on phenomena at the boundary of competence and performance. The course focuses on a number of structural/semantic phenomena of interest, selected from case-marking, agreement, long-distance dependencies, recursion, event-structure, and semantic/pragmatic factors in islandhood among others. It considers cases where some researchers have argued that competence and performance phenomena are linked, and it asks what implications these phenomena have for the theory of language.
The course will be offered in Fall, 2023. It is currently listed in the time schedule as occurring on Mondays from 1:30-4:30 but this timeframe will almost certainly change once it becomes clear who plans to take the course. If you are interested, please send email to firstname.lastname@example.org.
We are asking you to save the date for the 2023 IBACS Meet & Speak event on Friday, April 28th from 9-4:30pm. This exciting event will be in-person in Konover Auditorium.
Affiliated faculty will give 10-minute talks, most of which are on the research they have carried out, or propose carrying out, with seed funding awarded by IBACS. Affiliated graduate students who have received IBACS funding will present 5-minute “datablitz” style talks.
The event will provide an opportunity to learn more about the diverse interdisciplinary research of IBACS affiliates, provide a forum for cross-disciplinary networking, and will introduce our refurbished EEG Lab and our new UConn Science Alliance Mobile (SAM)!
9:15AM – Welcome
9:30AM – Panel Discussion
10:15AM – Faculty Talks
11:25AM – Graduate Student Data Blitz
12:00PM – Lunch
1:00PM – Keynote Speaker: Dr. Diego Bohorquez, Duke University
2:30PM to 4:30PM – Tours of the UConn Science Alliance Mobile (UConn SAM) and EEG Lab
A more detailed program including speaker names, talk titles, and the focus of the panel discussion will be shared soon.
We are excited to announce that Language Fest is making an in-person return for 2023, and invite you to join us on the afternoon of Wednesday, April 26th (event times TBD).
Language Fest is a University-wide research conference that welcomes the full cross-disciplinary community of language researchers at UConn for a day of sharing results, ideas, methodologies, and fostering future interdisciplinary collaborations. Researchers from all disciplines of the language sciences and at all career stages are welcome and encouraged to submit their work.
Further details about submissions and registration will be provided in early-March 2023.
For any questions about Language Fest, please e-mail: email@example.com and visit our website https://languagefest.uconn.edu/.
We look forward to your attendance and participation!
The Cognitive Science Program invites you to a talk on 2/24!
Speaker: Dr. Thomas Naselaris, an Associate Professor from Department of Neuroscience at the University of Minnesota.
Time & Location: 4PM, Friday February 24th, 2023, in Oak Hall Room 117. Light refreshments will be provided.
Talk Title: “Why Do We Have Mental Images?”
Abstract: Everyone who experiences mental imagery is the world expert on the contents of their own mental images. We argue that this privileged perspective on one’s own mental images provides very limited understanding about the function of mental imagery, which can only be understood by proposing and testing hypotheses about the computational work that mental images do. We propose that mental imagery functions as a useful form of inference that is conditioned on visual beliefs. We implement this form of inference in a simple generative model of natural scenes, and show that it makes testable predictions about differences in tuning to seen and imagined features. We confirm these predictions with a large-scale fMRI experiment in which human brain activity was sampled while subjects generated hundreds of mental images. We speculate that ongoing mental imagery may impact the structure of noise correlations in the visual system, and present a preliminary analysis of the Natural Scenes Dataset that appears to be consistent with these speculations.
Bio: Thomas is an Associate Professor in the Department of Neuroscience at the University of Minnesota, and a member of the Medical Discovery Team on Optical Imaging and Brain Science at the Center for Magnetic Resonance Research. He is co-founder and currently Executive Chair of the Conference on Cognitive Computational Neuroscience.
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View the article Here
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