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<p class="MsoNormal"><span style="color:#212121">Just a reminder that the deadline to submit abstracts for our special issue of Linguistics Vanguard on the Implications of Neural Networks and other Learning Models for Linguistic Theory is in two weeks (July
1). More information below.<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Vsevolod (Volya) Kapatsinski<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Special collection: Implications of Neural Networks and other Learning Models for Linguistic Theory (more information here:<span class="apple-converted-space"> </span><a href="https://blogs.uoregon.edu/ublab/lmlt/" title="https://blogs.uoregon.edu/ublab/lmlt/"><span style="color:#0078D7">https://blogs.uoregon.edu/ublab/lmlt/</span></a>)<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Managing Editor: Vsevolod Kapatsinski (University of Oregon)<o:p></o:p></span></p>
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<span style="color:#212121">Co-editor: Gašper Beguš (University of California, Berkeley)<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">This <a href="https://www.degruyter.com/journal/key/lingvan/9/1/html#overview" title="https://www.degruyter.com/journal/key/lingvan/9/1/html#overview"><span style="color:#0078D7">Linguistics Vanguard</span></a> special collection
is motivated by the recent breakthroughs in the application of neural networks to language data. Linguistics Vanguard publishes short 3000-4000 word articles on cutting-edge topics in linguistics and neighboring areas. Inclusion of multimodal content designed
to integrate interactive content (including, but not limited to audio and video, images, maps, software code, raw data, hyperlinks to external databases, and any other media enhancing the traditional written word) is particularly encouraged. Special collections
contributors should follow general submission guidelines for the journal (<a href="https://www.degruyter.com/journal/key/lingvan/html#overview" title="https://www.degruyter.com/journal/key/lingvan/html#overview"><span style="color:#0078D7">https://www.degruyter.com/journal/key/lingvan/html#overview</span></a>).<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Overview of the special issue topic:<o:p></o:p></span></p>
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<span style="color:#212121">Neural network models of language have been around for several decades, and became the de facto standard in psycholinguistics by the 1990s. There have also been several important attempts to incorporate neural network insights into
linguistic theory (e.g., Bates & MacWhinney, 1989; Bybee, 1985; Bybee & McClelland, 2005; Heitmeier et al., 2021; Smolensky & Legendre, 2006).<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">However, until recently, neural network models did not approximate the generative capacity of a human speaker or writer. This changed in the last few years, when large language models (e.g., the GPT family), embodying largely the
same principles but trained on vastly larger amounts of data, have made a breakthrough so that the language they generate is now usually indistinguishable from that generated by a human.<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">The accomplishments of these models have led to both calls for further integration between linguistic theory and neural networks (Beguš 2020; Kapatsinski, 2023; Kirov & Cotterell, 2018; Pater, 2019; Piantadosi, 2023) and criticism
suggesting that the way they work is fundamentally unlike human language learning and processing (e.g., Bender et al., 2021; Chomsky et al., 2023).<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">The present special collection for Linguistics Vanguard aims to foster a productive discussion between linguists, cognitive scientists, neural network modelers, neuroscientists, and proponents of other approaches to learning theory
(e.g., Bayesian probabilistic inference, instance-based lazy learning, reinforcement learning, active inference; Jamieson et al., 2022; Tenenbaum et al., 2011; Sajid et al., 2021). We call for contributions addressing the central question of linguistic theory
— Why are languages the way they are? – by means of a computational modeling approach. Reflections and position papers motivating the best ways to approach this question computationally are also welcome.<o:p></o:p></span></p>
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<span style="color:#212121">The contributions are encouraged to compare different models trained on the same data approximating human experience. Insightful position papers will also be accepted. Contributions should explicitly address the ways in which the
training data of the model(s) they discuss resembles and differs from human experience. Contributions can involve either hypothesis testing via minimally different versions of the same well-motivated model (e.g., Kapatsinski, 2023), or comparisons of state-of-the-art
models from different intellectual traditions (e.g., Albright & Hayes, 2003; Sajid et al., 2021) on how well they answer the question above.<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Research topics within this broad topic include:<o:p></o:p></span></p>
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<span style="color:#212121">1) the learning mechanisms and biases needed for modeling humanlike processing from humanlike experience<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:#212121">2) biases and mechanisms required for modeling trajectories of language change through iterated learning and/or use, or linguistic typology<o:p></o:p></span></p>
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<span style="color:#212121">More information is available here:<span class="apple-converted-space"> </span><a href="https://blogs.uoregon.edu/ublab/lmlt/" title="https://blogs.uoregon.edu/ublab/lmlt/"><span style="color:#0078D7">https://blogs.uoregon.edu/ublab/lmlt/</span></a><o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Contributors are asked to submit a one-page non-anonymous abstract (plus one page for figures and references) in .pdf format via the following link <a href="https://oregon.qualtrics.com/jfe/form/SV_e8LaCg8EqKHzjQG" title="https://oregon.qualtrics.com/jfe/form/SV_e8LaCg8EqKHzjQG"><span style="color:#0078D7">https://oregon.qualtrics.com/jfe/form/SV_e8LaCg8EqKHzjQG</span></a>.<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">The abstract should have the title as the top line, author names, affiliations and emails as the second line, and the body of the abstract as a separate paragraph (or three). Please contact managing editor Vsevolod (Volya) Kapatsinski, <a href="mailto:vkapatsi@uoregon.edu" title="mailto:vkapatsi@uoregon.edu"><span style="color:#0078D7">vkapatsi@uoregon.edu</span></a> with
any questions.<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Abstracts will be evaluated for topic relevance for the special collection, and on overall quality. Contributors of selected abstracts will be invited to submit a full paper (3000-4000 words) that will undergo peer review.<o:p></o:p></span></p>
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<span style="color:#212121"> <o:p></o:p></span></p>
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<span style="color:#212121">Timeline:<o:p></o:p></span></p>
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<span style="color:#212121">abstract due by July 1, 2024<o:p></o:p></span></p>
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<span style="color:#212121">notification of authors by August 1, 2024<o:p></o:p></span></p>
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<span style="color:#212121">full paper due by November 1, 2024<o:p></o:p></span></p>
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<span style="color:#212121">reviews to be completed by January 31, 2025<o:p></o:p></span></p>
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<span style="color:#212121">publication by March 2025<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">Best,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">Volya<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">-- <o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">Vsevolod Kapatsinski<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">Professor<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">Department of Linguistics, University of Oregon
<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">visiting at Department of English, University of Freiburg<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">Area Editor,
<i>Linguistics Vanguard</i> (cog, exp, comp)<o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-family:"Calibri",sans-serif;mso-ligatures:none">blogs.uoregon.edu/ublab/</span><o:p></o:p></p>
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