1,393 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Mapping the Focal Points of WordPress: A Software and Critical Code Analysis
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
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
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
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
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
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
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
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
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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