1,393 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Mapping the Focal Points of WordPress: A Software and Critical Code Analysis

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    Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected vulnerabilities. An examination of the influence of digital and computational thinking follows this. The work also explores the intersection of code patching and vulnerability management and how code shapes our sense of control, trust, and empathy, ultimately arguing that a rhetorical-cultural lens can be used to better understand code\u27s controlling influence. Recurring themes throughout these analyses and observations are the connections to power and vulnerability in WordPress\u27 code and how cultural, processual, rhetorical, and ethical implications can be expressed through its code, creating a particular worldview. Code\u27s emergent properties help illustrate how human values and practices (e.g., empathy, aesthetics, language, and trust) become encoded in software design and how people perceive the software through its worldview. These connected analyses reveal cultural, processual, and vulnerability focal points and the influence these entanglements have concerning WordPress as code, software, and platform. WordPress is a complex sociotechnical platform worthy of further study, as is the interdisciplinary merging of theoretical perspectives and disciplines to critically examine code. Ultimately, this project helps further enrich the field by introducing focal points in code, examining sociocultural phenomena within the code, and offering techniques to apply critical code methods

    2017 GREAT Day Program

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    SUNY Geneseo’s Eleventh Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1011/thumbnail.jp

    Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey

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    With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as BERT, ViT, GPT, etc. Inspired by the success of these models in single domains (like computer vision and natural language processing), the multi-modal pre-trained big models have also drawn more and more attention in recent years. In this work, we give a comprehensive survey of these models and hope this paper could provide new insights and helps fresh researchers to track the most cutting-edge works. Specifically, we firstly introduce the background of multi-modal pre-training by reviewing the conventional deep learning, pre-training works in natural language process, computer vision, and speech. Then, we introduce the task definition, key challenges, and advantages of multi-modal pre-training models (MM-PTMs), and discuss the MM-PTMs with a focus on data, objectives, network architectures, and knowledge enhanced pre-training. After that, we introduce the downstream tasks used for the validation of large-scale MM-PTMs, including generative, classification, and regression tasks. We also give visualization and analysis of the model parameters and results on representative downstream tasks. Finally, we point out possible research directions for this topic that may benefit future works. In addition, we maintain a continuously updated paper list for large-scale pre-trained multi-modal big models: https://github.com/wangxiao5791509/MultiModal_BigModels_SurveyComment: Accepted by Machine Intelligence Researc

    Relevance of parental monitoring strategies in explanation of externalising behaviour problems in adolescence: Mediation of parental knowledge

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    A process model of parental monitoring (PM) proposes that PM occurs in two distinct stages: before the adolescent goes out and when they return home. Parental and adolescent responses to monitoring interactions impact on future monitoring episodes. Research suggests that passive PM strategies (e.g. child disclosure) correlate with higher parental knowledge and less behavior problems. Self-reported measures were used on a sample of 507 Belgrade secondary school students (42.1% male) to examine the mediating effect (mediation analysis using JASP) of parental knowledge (the Scale of Parental Monitoring) on the relationship of PM strategies (Child Disclosure, Parental Solicitation and Parental Control) (the Scale of Parental Monitoring) with externalising problems (Aggressive and Rule-Breaking Behaviour) (ASEBA, YSR). The research results show that Parental Knowledge mediate the relation of Child Disclosure and RuleBreaking Behaviour (z = -6.544, p < .001) and Parental Control and Rule-Breaking Behaviour (z =-3.770, p< .001). No direct link between Parental Control and RuleBreaking Behavior, as well as Parental Solicitation and Rule-Breaking Behavior were established. Full mediation of the link between Child Disclosure and Aggressive Behavior by Parental Knowledge is found (total indirect effect z = -4.050, p < .001). The research results were discussed in the context of the relevance of the PM strategies for greater parental knowledge and prevention of externalising problems in adolescence

    Le goût d'Orval: constructing the taste of Orval beer through narratives

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    This study explores the construction of taste through narratives, using Orval beer as a case study. Often found on lists of the best or most unique beers in the world, Orval is a bottle conditioned, dry-hopped strong Belgian ale with Brettanomyces yeast, creating an orange-hue beer topped with a large volume of white foam. It is both easy to drink and complex in flavour. Made in southeastern Belgium within the walls of a Trappist Abbey, Orval is closely associated with the country of Belgium, a pilgrimage site for beer lovers because of its unique and diverse beer culture. In 2016 “Beer Culture in Belgium” was inscribed on UNESCO’s Representative List of Intangible Cultural Heritage of Humanity. Orval beer also carries the Authentic Trappist Product label, ensuring that this product is brewed under the supervision of Trappist monks or nuns, within the Abbey walls, and is non-profit. Additionally, the beer has a unique, distinctive taste. This dissertation explores narratives that tell of all these aspects. The first section, Narrating Belgium, examines how social and economic histories build Belgium as a beer nation, and how conversion narratives of Belgian beer enthusiasts support this theory. The Narrating Trappist section examines how the Legend of Orval and the history of Orval Abbey create a sense of place for Orval beer and how the Authentic Trappist Product label helps construct its terroir. The last section, Narrating Taste, focuses on narratives of taste as shared in online reviews of Orval beer. I first conduct lexical and network analysis of reviews on Untappd, RateBeer, and BeerAdvocate before focusing specifically on themes found in BeerAdvocate reviews. Through ethnographic and textual research, this dissertation introduces a folkloristic approach to taste and argues that both contextual and sensory elements are essential in building taste through narratives

    Musiktheorie als interdisziplinäres Fach: 8. Kongress der Gesellschaft für Musiktheorie Graz 2008

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    Im Oktober 2008 fand an der Universität für Musik und darstellende Kunst Graz (KUG) der 8. Kongress der Gesellschaft für Musiktheorie (GMTH) zum Thema »Musiktheorie als interdisziplinäres Fach« statt. Die hier vorgelegten gesammelten Beiträge akzentuieren Musiktheorie als multiperspektivische wissenschaftliche Disziplin in den Spannungsfeldern Theorie/Praxis, Kunst/Wissenschaft und Historik/Systematik. Die sechs Kapitel ergründen dabei die Grenzbereiche zur Musikgeschichte, Musikästhetik, zur Praxis musikalischer Interpretation, zur kompositorischen Praxis im 20. und 21. Jahrhundert, zur Ethnomusikologie sowie zur Systematischen Musikwissenschaft. Insgesamt 45 Aufsätze, davon 28 in deutscher, 17 in englischer Sprache, sowie die Dokumentation einer Podiumsdiskussion zeichnen in ihrer Gesamtheit einen höchst lebendigen und gegenwartsbezogenen Diskurs, der eine einzigartige Standortbestimmung des Fachs Musiktheorie bietet.The 8th congress of the Gesellschaft für Musiktheorie (GMTH) took place in October 2008 at the University for Music and Dramatic Arts Graz (KUG) on the topic »Music Theory and Interdisciplinarity«. The collected contributions characterize music theory as a multi-faceted scholarly discipline at the intersection of theory/practice, art/science and history/system. The six chapters explore commonalties with music history, music aesthetics, musical performance, compositional practice in twentieth- and twenty-first-century music, ethnomusicology and systematic musicology. A total of 45 essays (28 in German, 17 in English) and the documentation of a panel discussion form a vital discourse informed by contemporaneous issues of research in a broad number of fields, providing a unique overview of music theory today. A comprehensive English summary appears at the beginning of all contributions

    Large Language Model Alignment: A Survey

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    Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various concerns. The potential of these models is undeniably vast; however, they may yield texts that are imprecise, misleading, or even detrimental. Consequently, it becomes paramount to employ alignment techniques to ensure these models to exhibit behaviors consistent with human values. This survey endeavors to furnish an extensive exploration of alignment methodologies designed for LLMs, in conjunction with the extant capability research in this domain. Adopting the lens of AI alignment, we categorize the prevailing methods and emergent proposals for the alignment of LLMs into outer and inner alignment. We also probe into salient issues including the models' interpretability, and potential vulnerabilities to adversarial attacks. To assess LLM alignment, we present a wide variety of benchmarks and evaluation methodologies. After discussing the state of alignment research for LLMs, we finally cast a vision toward the future, contemplating the promising avenues of research that lie ahead. Our aspiration for this survey extends beyond merely spurring research interests in this realm. We also envision bridging the gap between the AI alignment research community and the researchers engrossed in the capability exploration of LLMs for both capable and safe LLMs.Comment: 76 page

    Relevance of parental monitoring strategies in explanation of externalising behaviour problems in adolescence: Mediation of parental knowledge

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    A process model of parental monitoring (PM) proposes that PM occurs in two distinct stages: before the adolescent goes out and when they return home. Parental and adolescent responses to monitoring interactions impact on future monitoring episodes. Research suggests that passive PM strategies (e.g. child disclosure) correlate with higher parental knowledge and less behavior problems. Self-reported measures were used on a sample of 507 Belgrade secondary school students (42.1% male) to examine the mediating effect (mediation analysis using JASP) of parental knowledge (the Scale of Parental Monitoring) on the relationship of PM strategies (Child Disclosure, Parental Solicitation and Parental Control) (the Scale of Parental Monitoring) with externalising problems (Aggressive and Rule-Breaking Behaviour) (ASEBA, YSR). The research results show that Parental Knowledge mediate the relation of Child Disclosure and RuleBreaking Behaviour (z = -6.544, p < .001) and Parental Control and Rule-Breaking Behaviour (z =-3.770, p< .001). No direct link between Parental Control and RuleBreaking Behavior, as well as Parental Solicitation and Rule-Breaking Behavior were established. Full mediation of the link between Child Disclosure and Aggressive Behavior by Parental Knowledge is found (total indirect effect z = -4.050, p < .001). The research results were discussed in the context of the relevance of the PM strategies for greater parental knowledge and prevention of externalising problems in adolescence

    Measuring the Severity of Depression from Text using Graph Representation Learning

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    The common practice of psychology in measuring the severity of a patient's depressive symptoms is based on an interactive conversation between a clinician and the patient. In this dissertation, we focus on predicting a score representing the severity of depression from such a text. We first present a generic graph neural network (GNN) to automatically rate severity using patient transcripts. We also test a few sequence-based deep models in the same task. We then propose a novel form for node attributes within a GNN-based model that captures node-specific embedding for every word in the vocabulary. This provides a global representation of each node, coupled with node-level updates according to associations between words in a transcript. Furthermore, we evaluate the performance of our GNN-based model on a Twitter sentiment dataset to classify three different sentiments and on Alzheimer's data to differentiate Alzheimer’s disease from healthy individuals respectively. In addition to applying the GNN model to learn a prediction model from the text, we provide post-hoc explanations of the model's decisions for all three tasks using the model's gradients
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