Difference between revisions of "Fall 2022 Schedule"
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| 02.16.22 || NO MEETING | | 02.16.22 || NO MEETING | ||
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− | | 02.23.22 || Invited talk: Aniello de Santo ( | + | | 02.23.22 || CompSem meetings go back to being hybrid! (Fleming 279 or https://cuboulder.zoom.us/j/97014876908) |
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+ | '''Invited talk: [https://aniellodesanto.github.io/about/ Aniello de Santo], University of Utah''' | ||
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+ | ''Bridging Typology and Learnability via Formal Language Theory'' | ||
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+ | The complexity of linguistic patterns is object of extensive debate in research programs focused on probing the inherent structure of human language abilities. But in what sense is a linguistic phenomenon more complex than another, and what can complexity tell us about the connection between linguistic typology and human cognition? In this talk, I overview a line of research approaching these questions from the perspective of recent advances in formal language theory. | ||
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+ | I will first broadly discuss how language theoretical characterizations allow us to focus on essential properties of linguistic patterns under study. I will emphasize how typological insights can help us refine existing mathematical characterizations, arguing for a two-way bridge between disciplines, and show how the theoretical predictions made by logic/algebraic formalization of typological generalizations can be used to test learning biases in humans (and machines). | ||
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+ | In doing so, I aim to illustrate the relevance of mathematically grounded approaches to cognitive investigations into linguistic generalizations, and thus further fruitful cross-disciplinary collaborations. | ||
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+ | '''Bio Sketch:''' | ||
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+ | Aniello De Santo is an Assistant Professor in the Linguistics Department at the University of Utah. | ||
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+ | Before joining Utah, he received a PhD in Linguistics from Stony Brook University. His research broadly lies at the intersection between computational, theoretical, and experimental linguistics. He is particularly interested in investigating how linguistic representations interact with general cognitive processes, with particular focus on sentence processing and learnability. In his past work, he has mostly made use of symbolic approaches grounded in formal language theory and rich grammar formalisms (Minimalist Grammars, Tree Adjoining Grammars). | ||
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|- style="border-top: 2px solid DarkGray;" | |- style="border-top: 2px solid DarkGray;" | ||
| 03.02.22 || Ghazaleh Kazeminejad, proposal defense | | 03.02.22 || Ghazaleh Kazeminejad, proposal defense |
Revision as of 11:36, 16 February 2022
Location: Hybrid (starting Feb 23) - Fleming 279, and the zoom link below
Time: Wednesdays at 10:30am, Mountain Time
Zoom link: https://cuboulder.zoom.us/j/97014876908
Date | Title |
---|---|
1.12.22 | Planning, introductions, welcome!
CompSem meetings will be virtual until further notice (https://cuboulder.zoom.us/j/97014876908) |
01.19.22 | Kai Larsen, CU Boulder Leeds School of Business
Validity in Design Research Research in design science has always recognized the importance of evaluating its knowledge outcomes, particularly of assessing the efficacy, utility, and attributes of the artifacts produced (e.g., A.I. systems, machine learning models, theories, frameworks). However, demonstrating the validity of design science research (DSR) is challenging and not well understood. This paper defines DSR validity and proposes a DSR Validity Framework. We evaluate the framework by assembling and analyzing an extensive data set of research validities papers from various disciplines, including design science. We then analyze the use of validity concepts in DSR and validate the framework. The results demonstrate that the DSR Validity Framework may be used to guide how validity can, and should, be used as an integral aspect of design science research. We further describe the steps for selecting appropriate validities for projects and formulate efficacy validity and characteristic validity claims suitable for inclusion in manuscripts. Keywords: Design science research (DSR), research validity, validity framework, artifact, evaluation, efficacy validity, characteristic validity. |
01.26.22 | Elizabeth Spaulding, prelim
Prelim topic: Evaluation for Abstract Meaning Representations Abstract Meaning Representation (AMR) is a semantic representation language that provides a way to represent the meaning of a sentence in the form of a graph. The task of AMR parsing—automatically extracting AMR graphs from natural language text—necessitates evaluation metrics to develop neural parsers. My prelim is a review of AMR evaluation metrics and the strengths and weaknesses of each approach, as well as a discussion of gaps and unexplored questions in the current literature. |
02.02.22 | NO MEETING |
02.09.22 | SCiL live session! |
02.16.22 | NO MEETING |
02.23.22 | CompSem meetings go back to being hybrid! (Fleming 279 or https://cuboulder.zoom.us/j/97014876908)
Bridging Typology and Learnability via Formal Language Theory The complexity of linguistic patterns is object of extensive debate in research programs focused on probing the inherent structure of human language abilities. But in what sense is a linguistic phenomenon more complex than another, and what can complexity tell us about the connection between linguistic typology and human cognition? In this talk, I overview a line of research approaching these questions from the perspective of recent advances in formal language theory. I will first broadly discuss how language theoretical characterizations allow us to focus on essential properties of linguistic patterns under study. I will emphasize how typological insights can help us refine existing mathematical characterizations, arguing for a two-way bridge between disciplines, and show how the theoretical predictions made by logic/algebraic formalization of typological generalizations can be used to test learning biases in humans (and machines). In doing so, I aim to illustrate the relevance of mathematically grounded approaches to cognitive investigations into linguistic generalizations, and thus further fruitful cross-disciplinary collaborations.
Aniello De Santo is an Assistant Professor in the Linguistics Department at the University of Utah. Before joining Utah, he received a PhD in Linguistics from Stony Brook University. His research broadly lies at the intersection between computational, theoretical, and experimental linguistics. He is particularly interested in investigating how linguistic representations interact with general cognitive processes, with particular focus on sentence processing and learnability. In his past work, he has mostly made use of symbolic approaches grounded in formal language theory and rich grammar formalisms (Minimalist Grammars, Tree Adjoining Grammars). |
03.02.22 | Ghazaleh Kazeminejad, proposal defense |
03.09.22 | Kevin Cohen |
03.16.22 | Chelsea Chandler, defense (TBC) |
03.23.22 | ***Spring Break*** |
03.30.22 | CLASIC Open House |
04.06.22 | Abteen Ebrahimi, prelim (TBC) |
04.13.22 | Ananya Ganesh, prelim (TBC) |
04.20.22 | Adam Wiemerslage, prelim (TBC) |
04.27.22 | Sagi Shaier, prelim (TBC) |
Past Schedules
- Fall 2021 Schedule
- Spring 2021 Schedule
- Fall 2020 Schedule
- Spring 2020 Schedule
- Fall 2019 Schedule
- Spring 2019 Schedule
- Fall 2018 Schedule
- Summer 2018 Schedule
- Spring 2018 Schedule
- Fall 2017 Schedule
- Summer 2017 Schedule
- Spring 2017 Schedule
- Fall 2016 Schedule
- Spring 2016 Schedule
- Fall 2015 Schedule
- Spring 2015 Schedule
- Fall 2014 Schedule
- Spring 2014 Schedule
- Fall 2013 Schedule
- Summer 2013 Schedule
- Spring 2013 Schedule
- Fall 2012 Schedule
- Spring 2012 Schedule
- Fall 2011 Schedule
- Summer 2011 Schedule
- Spring 2011 Schedule
- Fall 2010 Schedule
- Summer 2010 Schedule
- Spring 2010 Schedule
- Fall 2009 Schedule
- Summer 2009 Schedule
- Spring 2009 Schedule
- Fall 2008 Schedule
- Summer 2008 Schedule