Tootfinder

Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration
Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro
https://arxiv.org/abs/2404.05270

Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration
Algorithmic Recourse aims to provide actionable explanations, or recourse plans, to overturn potentially unfavourable decisions taken by automated machine learning models. In this paper, we propose an interaction paradigm based on a guided interaction pattern aimed at both eliciting the users' preferences and heading them toward effective recourse interventions. In a fictional task of money lending, we compare this approach with an exploratory interaction pattern based on a combination of alter…

Preliminary Guidelines For Combining Data Integration and Visual Data Analysis
Adam Coscia, Ashley Suh, Remco Chang, Alex Endert
https://arxiv.org/abs/2403.04757

Preliminary Guidelines For Combining Data Integration and Visual Data Analysis
Data integration is often performed to consolidate information from multiple disparate data sources during visual data analysis. However, integration operations are usually separate from visual analytics operations such as encode and filter in both interface design and empirical research. We conducted a preliminary user study to investigate whether and how data integration should be incorporated directly into the visual analytics process. We used two interface alternatives featuring contrasting…

Introducing cosmosGPT: Monolingual Training for Turkish Language Models
H. Toprak Kesgin, M. Kaan Yuce, Eren Dogan, M. Egemen Uzun, Atahan Uz, H. Emre Seyrek, Ahmed Zeer, M. Fatih Amasyali
https://arxiv.org/abs/2404.17336

Introducing cosmosGPT: Monolingual Training for Turkish Language Models
The number of open source language models that can produce Turkish is increasing day by day, as in other languages. In order to create the basic versions of such models, the training of multilingual models is usually continued with Turkish corpora. The alternative is to train the model with only Turkish corpora. In this study, we first introduce the cosmosGPT models that we created with this alternative method. Then, we introduce new finetune datasets for basic language models to fulfill user r…

#bitBlog Introducing HTTPie Desktop https://blog.bitexpert.de/blog/introducing_httpie_desktop

Introducing HTTPie Desktop | bitExpert
Discover the advantages of using httpie as a superior alternative to curl for communicating with external APIs. Explore the httpie desktop version that offers a comprehensive and user-friendly syntax, enabling you to efficiently organize your requests in spaces, collections, and tabs.

Artificial intelligence for context-aware visual change detection in software test automation
Milad Moradi, Ke Yan, David Colwell, Rhona Asgari
https://arxiv.org/abs/2405.00874

Artificial intelligence for context-aware visual change detection in software test automation
Automated software testing is integral to the software development process, streamlining workflows and ensuring product reliability. Visual testing within this context, especially concerning user interface (UI) and user experience (UX) validation, stands as one of crucial determinants of overall software quality. Nevertheless, conventional methods like pixel-wise comparison and region-based visual change detection fall short in capturing contextual similarities, nuanced alterations, and underst…

Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability
Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai, Xiao-Ming Wu
https://arxiv.org/abs/2403.18462

Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability
This study examines the decoy effect's underexplored influence on user search interactions and methods for measuring information retrieval (IR) systems' vulnerability to this effect. It explores how decoy results alter users' interactions on search engine result pages, focusing on metrics like click-through likelihood, browsing time, and perceived document usefulness. By analyzing user interaction logs from multiple datasets, the study demonstrates that decoy results significantly affect users'…

60/ Das ist Daniel. Er ist 16. Man sieht ihn auch auf dem Bild 56/.
Ich habe ihn letztes Jahr zum ersten Mal fotografiert und dann immer mal wieder, ohne mitzukriegen, dass es dieselbe Person ist. Damals hatte ich mit ihm gesprochen und er hatte mir seinen Namen gesagt. Am Sonnabend habe ich gehört, wie er seinen Namen und sein Alter in einem Interview genannt hat. Während er weggetragen wurde. Dann konnte ich die Bilder zuordnen. Ich habe viele Bilder mit Schmerzgriffen von ihm. Es gibt absurde Szenen von der Elsenbrücke.
#LetzteGeneration

Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability
Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai, Xiao-Ming Wu
https://arxiv.org/abs/2403.18462

Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability
This study examines the decoy effect's underexplored influence on user search interactions and methods for measuring information retrieval (IR) systems' vulnerability to this effect. It explores how decoy results alter users' interactions on search engine result pages, focusing on metrics like click-through likelihood, browsing time, and perceived document usefulness. By analyzing user interaction logs from multiple datasets, the study demonstrates that decoy results significantly affect users'…

SwipeGANSpace: Swipe-to-Compare Image Generation via Efficient Latent Space Exploration
Yuto Nakashima, Mingzhe Yang, Yukino Baba
https://arxiv.org/abs/2404.19693 https://arxiv.org/pdf/2404.19693
arXiv:2404.19693v1 Announce Type: new
Abstract: Generating preferred images using generative adversarial networks (GANs) is challenging owing to the high-dimensional nature of latent space. In this study, we propose a novel approach that uses simple user-swipe interactions to generate preferred images for users. To effectively explore the latent space with only swipe interactions, we apply principal component analysis to the latent space of the StyleGAN, creating meaningful subspaces. We use a multi-armed bandit algorithm to decide the dimensions to explore, focusing on the preferences of the user. Experiments show that our method is more efficient in generating preferred images than the baseline methods. Furthermore, changes in preferred images during image generation or the display of entirely different image styles were observed to provide new inspirations, subsequently altering user preferences. This highlights the dynamic nature of user preferences, which our proposed approach recognizes and enhances.

This https://arxiv.org/abs/2310.09611 has been replaced.
link: https://scholar.google.com/scholar?q=a

VizAbility: Enhancing Chart Accessibility with LLM-based Conversational Interaction
Traditional accessibility methods like alternative text and data tables typically underrepresent data visualization's full potential. Keyboard-based chart navigation has emerged as a potential solution, yet efficient data exploration remains challenging. We present VizAbility, a novel system that enriches chart content navigation with conversational interaction, enabling users to use natural language for querying visual data trends. VizAbility adapts to the user's navigation context for improve…