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added hey dashboard preprint
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---
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layout: publication
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# The quotes make the : possible, otherwise you can do it without quotes
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title: "Hey Dashboard!: Supporting Voice, Text, and Pointing Modalities in Dashboard Onboarding"
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key: 2025_hey_dashboard
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# paper | preprint | poster
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type: preprint
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# optional url for a different site; defaults to data.jku-vds-lab.at
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#paper_content_url:
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# The shortname is used for auto-generated titels
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shortname: Hey Dashboard
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# add a 2:1 aspect ratio (e.g., width: 400px, height: 200px) to the folder /assets/images/papers/
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image: 2025_hey_dashboard_small.png
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# add a 2:1 aspect ratio teaser figure (e.g., width: 1200px, height: 600px) to the folder /assets/images/papers/
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image_large: 2025_hey_dashboard.png
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# Authors in the "database" can be used with just the key (lastname). Others can be written properly.
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authors:
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- dhanoa
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- Gabriela Molina León
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- Eve Hoggan
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- Eduard Gröller
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- streit
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- Niklas Elmqvist
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journal-short:
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year: 2025
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bibentry: preprint
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bib:
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journal:
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doi: 10.48550/arXiv.2510.12386
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url:
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volume:
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number:
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pages:
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month:
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preprint: https://arxiv.org/abs/2510.12386 # here you can put all preprint links (arxiv.org, osf.io,...)
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# Add things like "Best Paper Award at InfoVis 2099, selected out of 4000 submissions"
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award:
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non_group_project: False
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# Use if this paper is linked to an internal project. This will link to the project site
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project:
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# Use this if you have an external project website
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external-project:
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pdf: 2025_hey_dashboard.pdf
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# Link to the repository where the code is hostet
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code:
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videos:
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- name: "Paper Video"
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youtube-id:
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abstract: "Visualization dashboards are regularly used for data exploration and analysis, but their complex interactions and interlinked views often require time-consuming onboarding sessions from dashboard authors. Preparing these onboarding materials is labor-intensive and requires manual updates when dashboards change. Recent advances in multimodal interaction powered by large language models (LLMs) provide ways to support self-guided onboarding. We present DIANA (Dashboard Interactive Assistant for Navigation and Analysis), a multimodal dashboard assistant that helps users for navigation and guided analysis through chat, audio, and mouse-based interactions. Users can choose any interaction modality or a combination of them to onboard themselves on the dashboard. Each modality highlights relevant dashboard features to support user orientation. Unlike typical LLM systems that rely solely on text-based chat, DIANA combines multiple modalities to provide explanations directly in the dashboard interface. We conducted a qualitative user study to understand the use of different modalities for different types of onboarding tasks and their complexities."
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# After the --- you can put information that you want to appear on the website using markdown formatting or HTML. A good example are acknowledgements, extra references, an erratum, etc.
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---
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