Tootfinder

Navigating the Docker Ecosystem: A Comprehensive Taxonomy and Survey
Prathamesh Muzumdar, Amol Bhosale, Ganga Prasad Basyal, George Kurian
https://arxiv.org/abs/2403.17940

Navigating the Docker Ecosystem: A Comprehensive Taxonomy and Survey
The cloud computing landscape is rapidly expanding and growing in complexity. It has witnessed the emergence of Cloud Computing as a widely adopted model for efficiently processing large volumes of data by harnessing clusters of commodity computers. This evolution enables the handling of massive data through on-demand services, relying on numerous microservices with diverse dependencies. The technology of containers ensures secure storage, allowing for largescale data processing with high scala…

@… After subscribing to the forum, I would suggest going on with:
1. Opt-in for the *community* plugins-taxonomy
2. Opt-in for the *blocks* taxonomy, see https:…

🐳 Global conservation genomics of blue whales calls into question subspecies taxonomy and refines knowledge of population structure
https://zslpublications.onlinelibrary.wiley.com/doi/10.1111/acv.12935

Factors that Affect Personalization of Robots for Older Adults
Laura Stegner, Emmanuel Senft, Bilge Mutlu
https://arxiv.org/abs/2402.17769 https://<…

Factors that Affect Personalization of Robots for Older Adults
We introduce a taxonomy of important factors to consider when designing interactions with an assistive robot in a senior living facility. These factors are derived from our reflection on two field studies and are grouped into the following high-level categories: primary user (residents), care partners, robot, facility and external circumstances. We outline how multiple factors in these categories impact different aspects of personalization, such as adjusting interactions based on the unique nee…

The Interaction Fidelity Model: A Taxonomy to Distinguish the Aspects of Fidelity in Virtual Reality
Michael Bonfert, Thomas Muender, Ryan P. McMahan, Frank Steinicke, Doug Bowman, Rainer Malaka, Tanja D\"oring
https://arxiv.org/abs/2402.16665

The Interaction Fidelity Model: A Taxonomy to Distinguish the Aspects of Fidelity in Virtual Reality
Fidelity describes how closely a replication resembles the original. It can be helpful to analyze how faithful interactions in virtual reality (VR) are to a reference interaction. In prior research, fidelity has been restricted to the simulation of reality - also called realism. Our definition includes other reference interactions, such as superpowers or fiction. Interaction fidelity is a multilayered concept. Unfortunately, different aspects of fidelity have either not been distinguished in sc…

🐳 Global conservation genomics of blue whales calls into question subspecies taxonomy and refines knowledge of population structure
https://zslpublications.onlinelibrary.wiley.com/doi/10.1111/acv.12935

Dear #WordPress flat mates, where did we put our contextual query block?
You know. The block, that is capable to query posts based on the context it is placed in. This better, related posts query block variation that can show posts by the current author, a given taxonomy or the current post_parent. The one, that doesn’t need any ID, but the object-field to contextualize for any of the query b…

This https://arxiv.org/abs/2402.13405 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

A Unified Taxonomy-Guided Instruction Tuning Framework for Entity Set Expansion and Taxonomy Expansion
Entity Set Expansion, Taxonomy Expansion, and Seed-Guided Taxonomy Construction are three representative tasks that can be used to automatically populate an existing taxonomy with new entities. However, previous approaches often address these tasks separately with heterogeneous techniques, lacking a unified perspective. To tackle this issue, in this paper, we identify the common key skills needed for these tasks from the view of taxonomy structures -- finding 'siblings' and finding 'parents' --…

(Un)making AI Magic: a Design Taxonomy
Maria Luce Lupetti, Dave Murray-Rust
https://arxiv.org/abs/2403.15216 https://arxiv.org/pdf/24…

(Un)making AI Magic: a Design Taxonomy
This paper examines the role that enchantment plays in the design of AI things by constructing a taxonomy of design approaches that increase or decrease the perception of magic and enchantment. We start from the design discourse surrounding recent developments in AI technologies, highlighting specific interaction qualities such as algorithmic uncertainties and errors and articulating relations to the rhetoric of magic and supernatural thinking. Through analyzing and reflecting upon 52 students'…

This https://arxiv.org/abs/2305.03803 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

A Survey of Trojans in Neural Models of Source Code: Taxonomy and Techniques
In this work, we study literature in Explainable AI and Safe AI to understand poisoning of neural models of code. In order to do so, we first establish a novel taxonomy for Trojan AI for code, and present a new aspect-based classification of triggers in neural models of code. Next, we highlight recent works that help us deepen our conception of how these models understand software code. Then we pick some of the recent, state-of-art poisoning strategies that can be used to manipulate such models…

Toward a Quantum Information System Cybersecurity Taxonomy and Testbed: Exploiting a Unique Opportunity for Early Impact
Benjamin Blakely, Joaquin Chung, Alec Poczatek, Ryan Syed, Raj Kettimuthu
https://arxiv.org/abs/2404.12465

Toward a Quantum Information System Cybersecurity Taxonomy and Testbed: Exploiting a Unique Opportunity for Early Impact
Any human-designed system can potentially be exploited in ways that its designers did not envision, and information systems or networks using quantum components do not escape this reality. We are presented with a unique but quickly waning opportunity to bring cybersecurity concerns to the forefront for quantum information systems before they become widely deployed. The resources and knowledge required to do so, however, may not be common in the cybersecurity community. Yet, a nexus exist. Cyber…

Dear #WordPress flat mates, where did we put our contextual query block?
You know. The block, that is capable to query posts based on the context it is placed in. This better, related posts query block variation that can show posts by the current author, a given taxonomy or the current post_parent. The one, that doesn’t need any ID, but the object-field to contextualize for any of the query b…

Caught up with my favorite photog (who thinks I’m a genius) at Guru Doughnuts, and learned at #Hackfort that a) the Whorfian Hypothesis is not relevant to the #LLM field, and b) a taxonomy of gibberish is needed.
#Treefort2024

This https://arxiv.org/abs/2402.05355 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Survey on Safe Multi-Modal Learning System
In the rapidly evolving landscape of artificial intelligence, multimodal learning systems (MMLS) have gained traction for their ability to process and integrate information from diverse modality inputs. Their expanding use in vital sectors such as healthcare has made safety assurance a critical concern. However, the absence of systematic research into their safety is a significant barrier to progress in this field. To bridge the gap, we present the first taxonomy that systematically categorizes…

My evening so far, after encountering a rare event bug in a theme for a website I wrote and still manage, and spending some quality 1-on-1 time with the dusty PHP code:
Yep, 7 years ago, I overwrote that sexy string instead of appending the next term in the custom taxonomy to it 👻

Measuring Diversity of Game Scenarios
Yuchen Li, Ziqi Wang, Qingquan Zhang, Jialin Liu
https://arxiv.org/abs/2404.15192 https://arxiv…

Measuring Diversity of Game Scenarios
This survey comprehensively reviews the multi-dimensionality of game scenario diversity, spotlighting the innovative use of procedural content generation and other fields as cornerstones for enriching player experiences through diverse game scenarios. By traversing a wide array of disciplines, from affective modeling and multi-agent systems to psychological studies, our research underscores the importance of diverse game scenarios in gameplay and education. Through a taxonomy of diversity metri…

This https://arxiv.org/abs/2402.13405 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

A Unified Taxonomy-Guided Instruction Tuning Framework for Entity Set Expansion and Taxonomy Expansion
Entity Set Expansion, Taxonomy Expansion, and Seed-Guided Taxonomy Construction are three representative tasks that can be used to automatically populate an existing taxonomy with new entities. However, previous approaches often address these tasks separately with heterogeneous techniques, lacking a unified perspective. To tackle this issue, in this paper, we identify the common key skills needed for these tasks from the view of taxonomy structures -- finding 'siblings' and finding 'parents' --…

An Analysis of the Preferences of Distribution Indicators in Evolutionary Multi-Objective Optimization
Jes\'us Guillermo Falc\'on-Cardona, Mahboubeh Nezhadmoghaddam, Emilio Bernal-Zubieta
https://arxiv.org/abs/2403.14838

An Analysis of the Preferences of Distribution Indicators in Evolutionary Multi-Objective Optimization
The distribution of objective vectors in a Pareto Front Approximation (PFA) is crucial for representing the associated manifold accurately. Distribution Indicators (DIs) assess the distribution of a PFA numerically, utilizing concepts like distance calculation, Biodiversity, Entropy, Potential Energy, or Clustering. Despite the diversity of DIs, their strengths and weaknesses across assessment scenarios are not well-understood. This paper introduces a taxonomy for classifying DIs, followed by a…

The taxonomy of ownership, by the eloquent @…
https://www.citationneeded.news/we-need-to-talk-about-digital-ownership/

We need to talk about digital ownership
"Ownership" means ten different things to ten different people. Let's talk about what we actually want.

SoK: Comprehensive Analysis of Rug Pull Causes, Datasets, and Detection Tools in DeFi
Dianxiang Sun, Wei Ma, Liming Nie, Yang Liu
https://arxiv.org/abs/2403.16082

SoK: Comprehensive Analysis of Rug Pull Causes, Datasets, and Detection Tools in DeFi
Rug pulls pose a grave threat to the cryptocurrency ecosystem, leading to substantial financial loss and undermining trust in decentralized finance (DeFi) projects. With the emergence of new rug pull patterns, research on rug pull is out of state. To fill this gap, we first conducted an extensive analysis of the literature review, encompassing both scholarly and industry sources. By examining existing academic articles and industrial discussions on rug pull projects, we present a taxonomy inclu…

A Taxonomy of Ambiguity Types for NLP
Margaret Y. Li, Alisa Liu, Zhaofeng Wu, Noah A. Smith
https://arxiv.org/abs/2403.14072 https://…

A Taxonomy of Ambiguity Types for NLP
Ambiguity is an critical component of language that allows for more effective communication between speakers, but is often ignored in NLP. Recent work suggests that NLP systems may struggle to grasp certain elements of human language understanding because they may not handle ambiguities at the level that humans naturally do in communication. Additionally, different types of ambiguity may serve different purposes and require different approaches for resolution, and we aim to investigate how lang…

Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy
SeongKu Kang, Shivam Agarwal, Bowen Jin, Dongha Lee, Hwanjo Yu, Jiawei Han
https://arxiv.org/abs/2403.04160

Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy
Document retrieval has greatly benefited from the advancements of large-scale pre-trained language models (PLMs). However, their effectiveness is often limited in theme-specific applications for specialized areas or industries, due to unique terminologies, incomplete contexts of user queries, and specialized search intents. To capture the theme-specific information and improve retrieval, we propose to use a corpus topical taxonomy, which outlines the latent topic structure of the corpus while r…

A Legal Risk Taxonomy for Generative Artificial Intelligence
David Atkinson, Jacob Morrison
https://arxiv.org/abs/2404.09479 https://…

A Legal Risk Taxonomy for Generative Artificial Intelligence
For the first time, this paper presents a taxonomy of legal risks associated with generative AI (GenAI) by breaking down complex legal concepts to provide a common understanding of potential legal challenges for developing and deploying GenAI models. The methodology is based on (1) examining the legal claims that have been filed in existing lawsuits and (2) evaluating the reasonably foreseeable legal claims that may be filed in future lawsuits. First, we identified 22 lawsuits against prominent…

This https://arxiv.org/abs/2311.10219 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Measuring Moral Dimensions in Social Media with Mformer
The ever-growing textual records of contemporary social issues, often discussed online with moral rhetoric, present both an opportunity and a challenge for studying how moral concerns are debated in real life. Moral foundations theory is a taxonomy of intuitions widely used in data-driven analyses of online content, but current computational tools to detect moral foundations suffer from the incompleteness and fragility of their lexicons and from poor generalization across data domains. In this …

Super Mario in the Pernicious Kingdoms: Classifying glitches in old games
Llewellyn Forward, Io Limmer, Joseph Hallett, Dan Page
https://arxiv.org/abs/2404.14870

Super Mario in the Pernicious Kingdoms: Classifying glitches in old games
In a case study spanning four classic Super Mario games and the analysis of 237 known glitches within them, we classify a variety of weaknesses that are exploited by speedrunners to enable them to beat games quickly and in surprising ways. Using the Seven Pernicious Kingdoms software defect taxonomy and the Common Weakness Enumeration, we categorize the glitches by the weaknesses that enable them. We identify 7 new weaknesses that appear specific to games and which are not covered by current so…

Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook
Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, Yuxuan Liang
https://arxiv.org/abs/2402.19348

Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for sustainable development by harnessing the power of cross-domain data fusion from diverse sources (e.g., geographical, traffic, social media, and environmental data) and modalities (e.g., spatio-temporal, visual, and textual modalities). Recently, we are witnessing a rising trend that utilizes various deep-learning methods to facilitate cross-domain data fusion in smart cities. To this end, we propose the first su…

Artificial intelligence and illusions of understanding in scientific research | Nature
https://www.nature.com/articles/s41586-024-07146-0

Artificial intelligence and illusions of understanding in scientific research | Nature
Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of scientists’ visions for AI, observing that their appeal comes from promises to improve productivity and objectivity by overcoming human shortcomings. But proposed AI solutions can also exploit our cognitive limitations, making us vulnerable to ill…

This https://arxiv.org/abs/2201.07351 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Taxonomy of Testable HTML5 Canvas Issues
The HTML5 is widely used to display high quality graphics in web applications. However, the combination of web, GUI, and visual techniques that are required to build applications, together with the lack of testing and debugging tools, makes developing such applications very challenging. To help direct future research on testing applications, in this paper we present a taxonomy of testable issues. First, we extracted 2,403 -related issue reports from 1…

Designing a Taxonomy for Smart Tourism Tools
Ant\'onio Galv\~ao, Fernando Brito e Abreu, Jo\~ao Joanaz de Melo
https://arxiv.org/abs/2402.10830 https:/…

Designing a Taxonomy for Smart Tourism Tools
Smart tourism (ST) stems from the concepts of e-tourism - focused on the digitalization of processes within the tourism industry, and digital tourism - also considering the digitalization within the tourist experience. The earlier ST references found regard ST Destinations and emerge from the development of Smart Cities. Our initial literature review on the ST concept and Smart Tourism Tools (STT) revealed significant research uncertainties: ST is poorly defined and frequently linked to the c…

Concurrency Model of BDI Programming Frameworks: Why Should We Control It?
Martina Baiardi, Samuele Burattini, Giovanni Ciatto, Danilo Pianini, Andrea Omicini, Alessandro Ricci
https://arxiv.org/abs/2404.10421

Concurrency Model of BDI Programming Frameworks: Why Should We Control It?
We provide a taxonomy of concurrency models for BDI frameworks, elicited by analysing state-of-the-art technologies, and aimed at helping both BDI designers and developers in making informed decisions. Comparison among BDI technologies w.r.t. concurrency models reveals heterogeneous support, and low customisability.

Purpose for Open-Ended Learning Robots: A Computational Taxonomy, Definition, and Operationalisation
Gianluca Baldassarre, Richard J. Duro, Emilio Cartoni, Mehdi Khamassi, Alejandro Romero, Vieri Giuliano Santucci
https://arxiv.org/abs/2403.02514

Purpose for Open-Ended Learning Robots: A Computational Taxonomy, Definition, and Operationalisation
Autonomous open-ended learning (OEL) robots are able to cumulatively acquire new skills and knowledge through direct interaction with the environment, for example relying on the guidance of intrinsic motivations and self-generated goals. OEL robots have a high relevance for applications as they can use the autonomously acquired knowledge to accomplish tasks relevant for their human users. OEL robots, however, encounter an important limitation: this may lead to the acquisition of knowledge that …

This https://arxiv.org/abs/2304.11643 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Privacy Computing Meets Metaverse: Necessity, Taxonomy and Challenges
Metaverse, the core of the next-generation Internet, is a computer-generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and data-sensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. With the rapid development of emerging technologies including augmented reality, virtual reality and blockchain, the metaverse system is beco…

This https://arxiv.org/abs/2404.09894 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection
With the expanding application of Large Language Models (LLMs) in various domains, it becomes imperative to comprehensively investigate their unforeseen behaviors and consequent outcomes. In this study, we introduce and systematically explore the phenomenon of "glitch tokens", which are anomalous tokens produced by established tokenizers and could potentially compromise the models' quality of response. Specifically, we experiment on seven top popular LLMs utilizing three distinct tokenizers and…

Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches
V\'ictor A. Braberman, Flavia Bonomo-Braberman, Yiannis Charalambous, Juan G. Colonna, Lucas C. Cordeiro, Rosiane de Freitas
https://arxiv.org/abs/2404.09384

Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches
Prompting has become one of the main approaches to leverage emergent capabilities of Large Language Models [Brown et al. NeurIPS 2020, Wei et al. TMLR 2022, Wei et al. NeurIPS 2022]. During the last year, researchers and practitioners have been playing with prompts to see how to make the most of LLMs. By homogeneously dissecting 80 papers, we investigate in deep how software testing and verification research communities have been abstractly architecting their LLM-enabled solutions. More precise…

Taxonomy of Mathematical Plagiarism
Ankit Satpute, Andre Greiner-Petter, Noah Gießing, Isabel Beckenbach, Moritz Schubotz, Olaf Teschke, Akiko Aizawa, Bela Gipp
https://arXiv.org/abs/2401.16969

Taxonomy of Mathematical Plagiarism
Plagiarism is a pressing concern, even more so with the availability of large language models. Existing plagiarism detection systems reliably find copied and moderately reworded text but fail for idea plagiarism, especially in mathematical science, which heavily uses formal mathematical notation. We make two contributions. First, we establish a taxonomy of mathematical content reuse by annotating potentially plagiarised 122 scientific document pairs. Second, we analyze the best-performing appro…

What Makes Systemic Discrimination, "Systemic?" Exposing the Amplifiers of Inequity
David B. McMillon
https://arxiv.org/abs/2403.11028 https://…

What Makes Systemic Discrimination, "Systemic?" Exposing the Amplifiers of Inequity
Drawing on work spanning economics, public health, education, sociology, and law, I formalize theoretically what makes systemic discrimination "systemic." Injustices do not occur in isolation, but within a complex system of interdependent factors; and their effects may amplify as a consequence. I develop a taxonomy of these amplification mechanisms, connecting them to well-understood concepts in economics that are precise, testable and policy-oriented. This framework reveals that these amplific…

ClassiPyGRB: Machine Learning-Based Classification and Visualization of Gamma Ray Bursts using t-SNE
Keneth Garcia-Cifuentes, Rosa L. Becerra, Fabio De Colle
https://arxiv.org/abs/2404.06439

ClassiPyGRB: Machine Learning-Based Classification and Visualization of Gamma Ray Bursts using t-SNE
Gamma-ray burst (GRBs) are the brightest events in the universe. For decades, astrophysicists have known about their cosmological nature. Every year, space missions such as Fermi and SWIFT detect hundreds of them. In spite of this large sample, GRBs show a complex taxonomy in the first seconds after their appearance, which makes it very difficult to find similarities between them using conventional techniques. It is known that GRBs originate from the death of a massive star or from the merger o…

This https://arxiv.org/abs/2310.07879 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks
Privacy is a key principle for developing ethical AI technologies, but how does including AI technologies in products and services change privacy risks? We constructed a taxonomy of AI privacy risks by analyzing 321 documented AI privacy incidents. We codified how the unique capabilities and requirements of AI technologies described in those incidents generated new privacy risks, exacerbated known ones, or otherwise did not meaningfully alter the risk. We present 12 high-level privacy risks tha…

This https://arxiv.org/abs/2304.11643 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Privacy Computing Meets Metaverse: Necessity, Taxonomy and Challenges
Metaverse, the core of the next-generation Internet, is a computer-generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and data-sensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. With the rapid development of emerging technologies including augmented reality, virtual reality and blockchain, the metaverse system is beco…

AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts
Shaona Ghosh, Prasoon Varshney, Erick Galinkin, Christopher Parisien
https://arxiv.org/abs/2404.05993

AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts
As Large Language Models (LLMs) and generative AI become more widespread, the content safety risks associated with their use also increase. We find a notable deficiency in high-quality content safety datasets and benchmarks that comprehensively cover a wide range of critical safety areas. To address this, we define a broad content safety risk taxonomy, comprising 13 critical risk and 9 sparse risk categories. Additionally, we curate AEGISSAFETYDATASET, a new dataset of approximately 26, 000 hum…

TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision
Yunyi Zhang, Ruozhen Yang, Xueqiang Xu, Jinfeng Xiao, Jiaming Shen, Jiawei Han
https://arxiv.org/abs/2403.00165

TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision
Hierarchical text classification aims to categorize each document into a set of classes in a label taxonomy. Most earlier works focus on fully or semi-supervised methods that require a large amount of human annotated data which is costly and time-consuming to acquire. To alleviate human efforts, in this paper, we work on hierarchical text classification with the minimal amount of supervision: using the sole class name of each node as the only supervision. Recently, large language models (LLM) s…

This https://arxiv.org/abs/2310.19778 has been replaced.
link: https://scholar.google.com/scholar?q=a

Human-AI collaboration is not very collaborative yet: A taxonomy of interaction patterns in AI-assisted decision making from a systematic review
Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI solutions for seamless integration with existing processes. Determining what information AI should provide to aid humans is vital, a concept underscored by explainable AI's efforts to justify AI prediction…

This https://arxiv.org/abs/2402.10830 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Designing a Taxonomy for Smart Tourism Tools
Smart tourism (ST) stems from the concepts of e-tourism - focused on the digitalization of processes within the tourism industry, and digital tourism - also considering the digitalization within the tourist experience. The earlier ST references found regard ST Destinations and emerge from the development of Smart Cities. Our initial literature review on the ST concept and Smart Tourism Tools (STT) revealed significant research uncertainties: ST is poorly defined and frequently linked to the c…

A compendium and evaluation of taxonomy quality attributes
Michael Unterkalmsteiner, Waleed Adbeen
https://arxiv.org/abs/2403.00111 https://

A compendium and evaluation of taxonomy quality attributes
Introduction: Taxonomies capture knowledge about a particular domain in a succinct manner and establish a common understanding among peers. Researchers use taxonomies to convey information about a particular knowledge area or to support automation tasks, and practitioners use them to enable communication beyond organizational boundaries. Aims: Despite this important role of taxonomies in software engineering, their quality is seldom evaluated. Our aim is to identify and define taxonomy quality …

This https://arxiv.org/abs/2310.17534 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

SoK: Pitfalls in Evaluating Black-Box Attacks
Numerous works study black-box attacks on image classifiers. However, these works make different assumptions on the adversary's knowledge and current literature lacks a cohesive organization centered around the threat model. To systematize knowledge in this area, we propose a taxonomy over the threat space spanning the axes of feedback granularity, the access of interactive queries, and the quality and quantity of the auxiliary data available to the attacker. Our new taxonomy provides three key…

IEEE-GDL CCD Smart Buildings Introduction
Victor Manuel Larios, Jos\'e Guadalupe Robledo, Leopoldo G\'omez, R. Rinc\'on
https://arxiv.org/abs/2403.13103

IEEE-GDL CCD Smart Buildings Introduction
As part of the activities of the IEEE-GDL CCD working group of physical infrastructure, this whitepaper is intented to be an initial guide to understand the layers, taxonomy of services and best practices for the development of smart buildings. Open standards are claimed in order to increase interoperability between layers and services. Moreover, two buildings in Guadalajara city, one new and another to renew, are described as a proof of concept under development and being part of the strategy …

Towards AI Safety: A Taxonomy for AI System Evaluation
Boming Xia, Qinghua Lu, Liming Zhu, Zhenchang Xing
https://arxiv.org/abs/2404.05388 https://<…

Towards AI Safety: A Taxonomy for AI System Evaluation
The advent of advanced AI brings to the forefront the need for comprehensive safety evaluation. However, divergent practices and terminologies across different communities (i.e., AI, software engineering, and governance), combined with the complexity of AI systems and environmental affordances (e.g., access to tools), call for a holistic evaluation approach. This paper proposes a framework for comprehensive AI system evaluation comprising three components: 1) harmonised terminology to facilitat…

This https://arxiv.org/abs/2402.01944 has been replaced.
link: https://scholar.google.com/scholar?q=a

Guarantees in Software Security
We review general approaches to reason about the security of a software system and reflect upon the guarantees they provide. We introduce a taxonomy of fundamental challenges towards the provision of guarantees, and discuss how these challenges are routinely exploited to attack a system in spite of credible assurances about the absence of such bugs. It is only when we identify, study, and acknowledge the flaws in our current reasoning systems today that we can develop effective mitigation strat…

Combined spin orientation and phase function of asteroids
B. Carry, J. Peloton, R. Le Montagner, M. Mahlke, J. Berthier
https://arxiv.org/abs/2403.20179 ht…

Combined spin orientation and phase function of asteroids
Large surveys provide numerous non-targeted observations of small bodies (SSOs). The upcoming LSST of the Rubin observatory will be the largest source of SSO photometry in the next decade. With non-coordinated epochs of observation, colors, and therefore taxonomy and composition, can only be computed by comparing absolute magnitudes obtained in each filter by solving the phase function (evolution of brightness of the small body against the solar phase angle). Current models in use in the commun…

Deep Configuration Performance Learning: A Systematic Survey and Taxonomy
Jingzhi Gong, Tao Chen
https://arxiv.org/abs/2403.03322 https://

Deep Configuration Performance Learning: A Systematic Survey and Taxonomy
Performance is arguably the most crucial attribute that reflects the behavior of a configurable software system. However, given the increasing scale and complexity of modern software, modeling and predicting how various configurations can impact performance becomes one of the major challenges in software maintenance. As such, performance is often modeled without having a thorough knowledge of the software system, but relying mainly on data, which fits precisely with the purpose of deep learning…

User Privacy Harms and Risks in Conversational AI: A Proposed Framework
Ece Gumusel, Kyrie Zhixuan Zhou, Madelyn Rose Sanfilippo
https://arxiv.org/abs/2402.09716

User Privacy Harms and Risks in Conversational AI: A Proposed Framework
This study presents a unique framework that applies and extends Solove (2006)'s taxonomy to address privacy concerns in interactions with text-based AI chatbots. As chatbot prevalence grows, concerns about user privacy have heightened. While existing literature highlights design elements compromising privacy, a comprehensive framework is lacking. Through semi-structured interviews with 13 participants interacting with two AI chatbots, this study identifies 9 privacy harms and 9 privacy risks in…

This https://arxiv.org/abs/2311.09761 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classification
We introduce MAFALDA, a benchmark for fallacy classification that merges and unites previous fallacy datasets. It comes with a taxonomy that aligns, refines, and unifies existing classifications of fallacies. We further provide a manual annotation of a part of the dataset together with manual explanations for each annotation. We propose a new annotation scheme tailored for subjective NLP tasks, and a new evaluation method designed to handle subjectivity. We then evaluate several language models…

This https://arxiv.org/abs/2403.00111 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

A compendium and evaluation of taxonomy quality attributes
Introduction: Taxonomies capture knowledge about a particular domain in a succinct manner and establish a common understanding among peers. Researchers use taxonomies to convey information about a particular knowledge area or to support automation tasks, and practitioners use them to enable communication beyond organizational boundaries. Aims: Despite this important role of taxonomies in software engineering, their quality is seldom evaluated. Our aim is to identify and define taxonomy quality …

Making High-Level AI Design Decisions Explicit Using a Binary Stream System-Designation Approach
Julia Mossbridge
https://arxiv.org/abs/2403.08832 https://…

Making High-Level AI Design Decisions Explicit Using a Binary Stream System-Designation Approach
Some crucial decisions in AI design tend to be overlooked or factor choices are assumed implicitly. The question often answered first is what the AI will do, not how it will interact with the rest of the world. This reduces our understanding of the possible types of AI that can be developed and their potential impacts on humanity. As an initial AI taxonomy, I present binary choices for 10 of the subjectively most separable and influential high-level design factors, then give brief examples of s…

This https://arxiv.org/abs/2401.06790 has been replaced.
link: https://scholar.google.com/scholar?q=a

Using Zero-shot Prompting in the Automatic Creation and Expansion of Topic Taxonomies for Tagging Retail Banking Transactions
This work presents an unsupervised method for automatically constructing and expanding topic taxonomies using instruction-based fine-tuned LLMs (Large Language Models). We apply topic modeling and keyword extraction techniques to create initial topic taxonomies and LLMs to post-process the resulting terms and create a hierarchy. To expand an existing taxonomy with new terms, we use zero-shot prompting to find out where to add new nodes, which, to our knowledge, is the first work to present such…

This https://arxiv.org/abs/2308.04522 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Deep Learning for Steganalysis of Diverse Data Types: A review of methods, taxonomy, challenges and future directions
Steganography and steganalysis are two interrelated aspects of the field of information security. Steganography seeks to conceal communications, whereas steganalysis is aimed to either find them or even, if possible, recover the data they contain. Steganography and steganalysis have attracted a great deal of interest, particularly from law enforcement. Steganography is often used by cybercriminals and even terrorists to avoid being captured while in possession of incriminating evidence, even en…

Understanding Cross-Lingual Alignment -- A Survey
Katharina H\"ammerl, Jind\v{r}ich Libovick\'y, Alexander Fraser
https://arxiv.org/abs/2404.06228

Understanding Cross-Lingual Alignment -- A Survey
Cross-lingual alignment, the meaningful similarity of representations across languages in multilingual language models, has been an active field of research in recent years. We survey the literature of techniques to improve cross-lingual alignment, providing a taxonomy of methods and summarising insights from throughout the field. We present different understandings of cross-lingual alignment and their limitations. We provide a qualitative summary of results from a large number of surveyed pape…

This https://arxiv.org/abs/1908.03591 has been replaced.
link: https://scholar.google.com/scholar?q=a

Toward a Taxonomy of Inventory Systems for Virtual Reality Games
Virtual reality (VR) games are gradually becoming more elaborated and feature-rich, but fail to reach the complexity of traditional digital games. One common feature that is used to extend and organize complex gameplay is the in-game inventory, which allows players to obtain and carry new tools and items throughout their journey. However, VR imposes additional requirements and challenges that impede the implementation of this important feature and hinder games to unleash their full potential. O…

What the Fix? A Study of ASATs Rule Documentation
Corentin LatappyLaBRI, Thomas DegueuleLaBRI, Jean-R\'emy FalleriLaBRI, Romain RobbesCNRS, LaBRI, UB, Bordeaux INP, Xavier Blanc, C\'edric Teyton
https://arxiv.org/abs/2402.08270

What the Fix? A Study of ASATs Rule Documentation
Automatic Static Analysis Tools (ASATs) are widely used by software developers to diffuse and enforce coding practices. Yet, we know little about the documentation of ASATs, despite it being critical to learn about the coding practices in the first place. We shed light on this through several contributions. First, we analyze the documentation of more than 100 rules of 16 ASATs for multiple programming languages, and distill a taxonomy of the purposes of the documentation-What triggers a rule; W…

"My toxic trait is thinking I'll remember this": gaps in the learner experience of video tutorials for feature-rich software
Ian Drosos, Advait Sarkar, Andrew D. Gordon
https://arxiv.org/abs/2404.07114

"My toxic trait is thinking I'll remember this": gaps in the learner experience of video tutorials for feature-rich software
Video tutorials are a popular medium for informal and formal learning. However, when learners attempt to view and follow along with these tutorials, they encounter what we call gaps, that is, issues that can prevent learning. We examine the gaps encountered by users of video tutorials for feature-rich software, such as spreadsheets. We develop a theory and taxonomy of such gaps, identifying how they act as barriers to learning, by collecting and analyzing 360 viewer comments from 90 Microsoft E…

This https://arxiv.org/abs/2403.01081 has been replaced.
link: https://scholar.google.com/scholar?q=a

LAB: Large-Scale Alignment for ChatBots
This work introduces LAB (Large-scale Alignment for chatBots), a novel methodology designed to overcome the scalability challenges in the instruction-tuning phase of large language model (LLM) training. Leveraging a taxonomy-guided synthetic data generation process and a multi-phase tuning framework, LAB significantly reduces reliance on expensive human annotations and proprietary models like GPT-4. We demonstrate that LAB-trained models can achieve competitive performance across several benchm…

This https://arxiv.org/abs/2107.08434 has been replaced.
link: https://scholar.google.com/scholar?q=a

"I Packed My Bag and in It I Put...": A Taxonomy of Inventory Systems for Virtual Reality Games
On a journey, a backpack is a perfect place to store and organize the necessary provisions and tools. Similarly, carrying and managing items is a central part of most digital games, providing significant prospects for the player experience. Even though VR games are gradually becoming more mature, most of them still avoid this essential feature. Some of the reasons for this deficit are the additional requirements and challenges that VR imposes on developers to achieve a compelling user experienc…

This https://arxiv.org/abs/2402.01944 has been replaced.
link: https://scholar.google.com/scholar?q=a

Guarantees in Software Security
We review general approaches to reason about the security of a software system and reflect upon the guarantees they provide. We introduce a taxonomy of fundamental challenges towards the provision of guarantees, and discuss how these challenges are routinely exploited to attack a system in spite of credible assurances about the absence of such bugs. It is only when we identify, study, and acknowledge the flaws in our current reasoning systems today that we can develop effective mitigation strat…

Efficient Online Crowdsourcing with Complex Annotations
Reshef Meir, Viet-An Nguyen, Xu Chen, Jagdish Ramakrishnan, Udi Weinsberg
https://arXiv.org/abs/2401.15116

Efficient Online Crowdsourcing with Complex Annotations
Crowdsourcing platforms use various truth discovery algorithms to aggregate annotations from multiple labelers. In an online setting, however, the main challenge is to decide whether to ask for more annotations for each item to efficiently trade off cost (i.e., the number of annotations) for quality of the aggregated annotations. In this paper, we propose a novel approach for general complex annotation (such as bounding boxes and taxonomy paths), that works in an online crowdsourcing setting. W…