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Surveyor: Facilitating Discovery Within Video Games for Blind and Low Vision Players arXiv.cs.HC Pub Date : 2024-03-15 Vishnu Nair, Hanxiu 'Hazel' Zhu, Peize Song, Jizhong Wang, Brian A. Smith
Video games are increasingly accessible to blind and low vision (BLV) players, yet many aspects remain inaccessible. One aspect is the joy players feel when they explore environments and make new discoveries, which is integral to many games. Sighted players experience discovery by surveying environments and identifying unexplored areas. Current accessibility tools, however, guide BLV players directly
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Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teams arXiv.cs.HC Pub Date : 2024-03-15 Vanessa Aisyahsari Hanschke, Dylan Rees, Merve Alanyali, David Hopkinson, Paul Marshall
Researchers urge technology practitioners such as data scientists to consider the impacts and ethical implications of algorithmic decisions. However, unlike programming, statistics, and data management, discussion of ethical implications is rarely included in standard data science training. To begin to address this gap, we designed and tested a toolbox called the data ethics emergency drill (DEED)
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Designing User-Centered Simulations of Leadership Situations for Cave Automatic Virtual Environments: Development and Usability Study arXiv.cs.HC Pub Date : 2024-03-15 Francesco Vona, Miladin Ćeranić, Irma Rybnikova, Jan-Niklas Voigt-Antons
Given that experience is a pivotal dimension of learning processes in the field of leadership, the ongoing and unresolved issue is how such experiential moments could be provided when developing leadership skills and competencies. Role-plays and business simulations are widely used in this context as they are said to teach relevant social leadership skills, like those required by everyday communication
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Unpacking ICT-supported Social Connections and Support of Late-life Migration: From the Lens of Social Convoys arXiv.cs.HC Pub Date : 2024-03-15 Ying Lei, Shuai Ma, Yuling Sun
Migration and aging-related dilemmas have limited the opportunities for late-life migrants to rebuild social connections and access support. While research on migrants has drawn increasing attention in HCI, limited attention has been paid to the increasing number of late-life migrants. This paper reports a qualitative study examining the social connections and support of late-life migrants. In particular
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CyberMoraba: A game-based approach enhancing cybersecurity awareness arXiv.cs.HC Pub Date : 2024-03-15 Mike Nkongolo
Numerous studies confirm Cybersecurity Awareness Games (CAGs) effectively bolster organisational security against cyberattacks. This article introduces a serious CAG, integrating the traditional South African Morabaraba board game into cybersecurity education. Players adopt roles of defenders or attackers, strategically placing tokens to enhance awareness. Evaluation shows positive outcomes, enhancing
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Trusting the Search: Unraveling Human Trust in Health Information from Google and ChatGPT arXiv.cs.HC Pub Date : 2024-03-15 Xin Sun, Rongjun Ma, Xiaochang Zhao, Zhuying Li, Janne Lindqvist, Abdallah El Ali, Jos A. Bosch
People increasingly rely on online sources for health information seeking due to their convenience and timeliness, traditionally using search engines like Google as the primary search agent. Recently, the emergence of generative Artificial Intelligence (AI) has made Large Language Model (LLM) powered conversational agents such as ChatGPT a viable alternative for health information search. However,
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eKichabi v2: Designing and Scaling a Dual-Platform Agricultural Technology in Rural Tanzania arXiv.cs.HC Pub Date : 2024-03-15 Ananditha Raghunath, Alexander Metzger, Hans Easton, XunMei Liu, Fanchong Wang, Yunqi Wang, Yunwei Zhao, Hosea Mpogole, Richard Anderson
Although farmers in Sub-Saharan Africa are accessing feature phones and smartphones at historically high rates, they face challenges finding a robust network of agricultural contacts. With collaborators, we conduct a quantitative survey of 1014 agricultural households in Kagera, Tanzania to characterize technology access, use, and comfort levels in the region. Recognizing the paucity of research on
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Influence of Personality and Communication Behavior of a Conversational Agent on User Experience and Social Presence in Augmented Reality arXiv.cs.HC Pub Date : 2024-03-14 Katerina Koleva, Maurizio Vergari, Tanja Kojić, Sebastian Möller, Jan-Niklas Voigt-Antons
A virtual embodiment can benefit conversational agents, but it is unclear how their personalities and non-verbal behavior influence the User Experience and Social Presence in Augmented Reality (AR). We asked 30 users to converse with a virtual assistant who gives recommendations about city activities. The participants interacted with two different personalities: Sammy, a cheerful blue mouse, and Olive
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The Influence of Extended Reality and Virtual Characters' Embodiment Levels on User Experience in Well-Being Activities arXiv.cs.HC Pub Date : 2024-03-14 Tanja Kojić, Maurizio Vergari, Marco Podratz, Sebastian Möller, Jan-Niklas Voigt-Antons
Millions of people have seen their daily habits transform, reducing physical activity and leading to mental health issues. This study explores how virtual characters impact motivation for well-being. Three prototypes with cartoon, robotic, and human-like avatars were tested by 22 participants. Results show that animated virtual avatars, especially with extended reality, boost motivation, enhance comprehension
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Evaluating the Application of Large Language Models to Generate Feedback in Programming Education arXiv.cs.HC Pub Date : 2024-03-13 Sven Jacobs, Steffen Jaschke
This study investigates the application of large language models, specifically GPT-4, to enhance programming education. The research outlines the design of a web application that uses GPT-4 to provide feedback on programming tasks, without giving away the solution. A web application for working on programming tasks was developed for the study and evaluated with 51 students over the course of one semester
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Effect of external characteristics of a virtual human being during the use of a computer-assisted therapy tool arXiv.cs.HC Pub Date : 2024-03-14 Navid Ashrafi, Vanessa Neuhaus, Francesco Vona, Nicolina Laura Peperkorn, Youssef Shiban, Jan-Niklas Voigt-Antons
Identification within media, whether with real or fictional characters, significantly impacts users, shaping their behavior and enriching their social and emotional experiences. Immersive media, like video games, utilize virtual entities such as agents, avatars, or NPCs to connect users with virtual worlds, fostering a heightened sense of immersion and identification. However, challenges arise in visually
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PrompTHis: Visualizing the Process and Influence of Prompt Editing during Text-to-Image Creation arXiv.cs.HC Pub Date : 2024-03-14 Yuhan Guo, Hanning Shao, Can Liu, Kai Xu, Xiaoru Yuan
Generative text-to-image models, which allow users to create appealing images through a text prompt, have seen a dramatic increase in popularity in recent years. However, most users have a limited understanding of how such models work and it often requires many trials and errors to achieve satisfactory results. The prompt history contains a wealth of information that could provide users with insights
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pARam: Leveraging Parametric Design in Extended Reality to Support the Personalization of Artifacts for Personal Fabrication arXiv.cs.HC Pub Date : 2024-03-14 Evgeny Stemasov, Simon Demharter, Max Rädler, Jan Gugenheimer, Enrico Rukzio
Extended Reality (XR) allows in-situ previewing of designs to be manufactured through Personal Fabrication (PF). These in-situ interactions exhibit advantages for PF, like incorporating the environment into the design process. However, design-for-fabrication in XR often happens through either highly complex 3D-modeling or is reduced to rudimentary adaptations of crowd-sourced models. We present pARam
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DungeonMaker: Embedding Tangible Creation and Destruction in Hybrid Board Games through Personal Fabrication Technology arXiv.cs.HC Pub Date : 2024-03-14 Evgeny Stemasov, Tobias Wagner, Ali Askari, Jessica Janek, Omid Rajabi, Anja Schikorr, Julian Frommel, Jan Gugenheimer, Enrico Rukzio
Hybrid board games (HBGs) augment their analog origins digitally (e.g., through apps) and are an increasingly popular pastime activity. Continuous world and character development and customization, known to facilitate engagement in video games, remain rare in HBGs. If present, they happen digitally or imaginarily, often leaving physical aspects generic. We developed DungeonMaker, a fabrication-augmented
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"Are You Really Sure?" Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision Making arXiv.cs.HC Pub Date : 2024-03-14 Shuai Ma, Xinru Wang, Ying Lei, Chuhan Shi, Ming Yin, Xiaojuan Ma
In AI-assisted decision-making, it is crucial but challenging for humans to achieve appropriate reliance on AI. This paper approaches this problem from a human-centered perspective, "human self-confidence calibration". We begin by proposing an analytical framework to highlight the importance of calibrated human self-confidence. In our first study, we explore the relationship between human self-confidence
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"Like a Nesting Doll": Analyzing Recursion Analogies Generated by CS Students using Large Language Models arXiv.cs.HC Pub Date : 2024-03-14 Seth Bernstein, Paul Denny, Juho Leinonen, Lauren Kan, Arto Hellas, Matt Littlefield Sami Sarsa, Stephen MacNeil
Grasping complex computing concepts often poses a challenge for students who struggle to anchor these new ideas to familiar experiences and understandings. To help with this, a good analogy can bridge the gap between unfamiliar concepts and familiar ones, providing an engaging way to aid understanding. However, creating effective educational analogies is difficult even for experienced instructors.
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Which Artificial Intelligences Do People Care About Most? A Conjoint Experiment on Moral Consideration arXiv.cs.HC Pub Date : 2024-03-14 Ali Ladak, Jamie Harris, Jacy Reese Anthis
Many studies have identified particular features of artificial intelligences (AI), such as their autonomy and emotion expression, that affect the extent to which they are treated as subjects of moral consideration. However, there has not yet been a comparison of the relative importance of features as is necessary to design and understand increasingly capable, multi-faceted AI systems. We conducted
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Machine Learning Processes as Sources of Ambiguity: Insights from AI Art arXiv.cs.HC Pub Date : 2024-03-14 Christian Sivertsen, Guido Salimbeni, Anders Sundnes Løvlie, Steve Benford, Jichen Zhu
Ongoing efforts to turn Machine Learning (ML) into a design material have encountered limited success. This paper examines the burgeoning area of AI art to understand how artists incorporate ML in their creative work. Drawing upon related HCI theories, we investigate how artists create ambiguity by analyzing nine AI artworks that use computer vision and image synthesis. Our analysis shows that, in
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VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture Videos arXiv.cs.HC Pub Date : 2024-03-14 Seulgi Choi, Hyewon Lee, Yoonjoo Lee, Juho Kim
The lengthy monologue-style online lectures cause learners to lose engagement easily. Designing lectures in a "vicarious dialogue" format can foster learners' cognitive activities more than monologue-style. However, designing online lectures in a dialogue style catered to the diverse needs of learners is laborious for instructors. We conducted a design workshop with eight educational experts and seven
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Towards Proactive Interactions for In-Vehicle Conversational Assistants Utilizing Large Language Models arXiv.cs.HC Pub Date : 2024-03-14 Huifang Du, Xuejing Feng, Jun Ma, Meng Wang, Shiyu Tao, Yijie Zhong, Yuan-Fang Li, Haofen Wang
Research demonstrates that the proactivity of in-vehicle conversational assistants (IVCAs) can help to reduce distractions and enhance driving safety, better meeting users' cognitive needs. However, existing IVCAs struggle with user intent recognition and context awareness, which leads to suboptimal proactive interactions. Large language models (LLMs) have shown potential for generalizing to various
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OutlineSpark: Igniting AI-powered Presentation Slides Creation from Computational Notebooks through Outlines arXiv.cs.HC Pub Date : 2024-03-14 Fengjie Wang, Yanna Lin, Leni Yang, Haotian Li, Mingyang Gu, Min Zhu, Huamin Qu
Computational notebooks are widely utilized for exploration and analysis. However, creating slides to communicate analysis results from these notebooks is quite tedious and time-consuming. Researchers have proposed automatic systems for generating slides from notebooks, which, however, often do not consider the process of users conceiving and organizing their messages from massive code cells. Those
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How do Older Adults Set Up Voice Assistants? Lessons Learned from a Deployment Experience for Older Adults to Set Up Standalone Voice Assistants arXiv.cs.HC Pub Date : 2024-03-14 Chen Chen, Ella T. Lifset, Yichen Han, Arkajyoti Roy, Michael Hogarth, Alison A. Moore, Emilia Farcas, Nadir Weibel
While standalone Voice Assistants (VAs) are promising to support older adults' daily routine and wellbeing management, onboarding and setting up these devices can be challenging. Although some older adults choose to seek assistance from technicians and adult children, easy set up processes that facilitate independent use are still critical, especially for those who do not have access to external resources
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset arXiv.cs.HC Pub Date : 2024-03-14 Hugo Laurençon, Léo Tronchon, Victor Sanh
Using vision-language models (VLMs) in web development presents a promising strategy to increase efficiency and unblock no-code solutions: by providing a screenshot or a sketch of a UI, a VLM could generate the code to reproduce it, for instance in a language like HTML. Despite the advancements in VLMs for various tasks, the specific challenge of converting a screenshot into a corresponding HTML has
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AI coach for badminton arXiv.cs.HC Pub Date : 2024-03-13 Dhruv Toshniwal, Arpit Patil, Nancy Vachhani
In the competitive realm of sports, optimal performance necessitates rigorous management of nutrition and physical conditioning. Specifically, in badminton, the agility and precision required make it an ideal candidate for motion analysis through video analytics. This study leverages advanced neural network methodologies to dissect video footage of badminton matches, aiming to extract detailed insights
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Exploring Prompt Engineering Practices in the Enterprise arXiv.cs.HC Pub Date : 2024-03-13 Michael Desmond, Michelle Brachman
Interaction with Large Language Models (LLMs) is primarily carried out via prompting. A prompt is a natural language instruction designed to elicit certain behaviour or output from a model. In theory, natural language prompts enable non-experts to interact with and leverage LLMs. However, for complex tasks and tasks with specific requirements, prompt design is not trivial. Creating effective prompts
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A Virtual Environment for Collaborative Inspection in Additive Manufacturing arXiv.cs.HC Pub Date : 2024-03-13 Vuthea Chheang, Brian Thomas Weston, Robert William Cerda, Brian Au, Brian Giera, Peer-Timo Bremer, Haichao Miao
Additive manufacturing (AM) techniques have been used to enhance the design and fabrication of complex components for various applications in the medical, aerospace, energy, and consumer products industries. A defining feature for many AM parts is the complex internal geometry enabled by the printing process. However, inspecting these internal structures requires volumetric imaging, i.e., X-ray CT
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Bury Me Here --The New Genre of Narrative Design Game Based on Immersive Storytelling arXiv.cs.HC Pub Date : 2024-03-13 Zhongsheng Li, Wuji Li, Yudong He
Virtual reality games always provide the player with the most verisimilitude experience. With the advancement of VR hardware, it may become mainstream how people feel and attach to a virtual world. The paper discusses a possible solution to finding a better balance between the two classical genres of VR games, sensory stimulation and storytelling. To this end, we designed a game named "Bury Me Here
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Making High-Level AI Design Decisions Explicit Using a Binary Stream System-Designation Approach arXiv.cs.HC Pub Date : 2024-03-12 Julia Mossbridge
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
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MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models arXiv.cs.HC Pub Date : 2024-03-14 Zunnan Xu, Yukang Lin, Haonan Han, Sicheng Yang, Ronghui Li, Yachao Zhang, Xiu Li
Gesture synthesis is a vital realm of human-computer interaction, with wide-ranging applications across various fields like film, robotics, and virtual reality. Recent advancements have utilized the diffusion model and attention mechanisms to improve gesture synthesis. However, due to the high computational complexity of these techniques, generating long and diverse sequences with low latency remains
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ShareYourReality: Investigating Haptic Feedback and Agency in Virtual Avatar Co-embodiment arXiv.cs.HC Pub Date : 2024-03-13 Karthikeya Puttur Venkatraj, Wo Meijer, Monica Perusquía-Hernández, Gijs Huisman, Abdallah El Ali
Virtual co-embodiment enables two users to share a single avatar in Virtual Reality (VR). During such experiences, the illusion of shared motion control can break during joint-action activities, highlighting the need for position-aware feedback mechanisms. Drawing on the perceptual crossing paradigm, we explore how haptics can enable non-verbal coordination between co-embodied participants. In a within-subjects
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Understanding Reader Takeaways in Thematic Maps Under Varying Text, Detail, and Spatial Autocorrelation arXiv.cs.HC Pub Date : 2024-03-13 Arlen Fan, Fan Lei, Michelle Mancenido, Alan MacEachren, Ross Maciejewski
Maps are crucial in conveying geospatial data in diverse contexts such as news and scientific reports. This research, utilizing thematic maps, probes deeper into the underexplored intersection of text framing and map types in influencing map interpretation. In this work, we conducted experiments to evaluate how textual detail and semantic content variations affect the quality of insights derived from
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Help Supporters: Exploring the Design Space of Assistive Technologies to Support Face-to-Face Help Between Blind and Sighted Strangers arXiv.cs.HC Pub Date : 2024-03-13 Yuanyang Teng, Connor Courtien, David Angel Rios, Yves M. Tseng, Jacqueline Gibson, Maryam Aziz, Avery Reyna, Rajan Vaish, Brian A. Smith
Blind and low-vision (BLV) people face many challenges when venturing into public environments, often wishing it were easier to get help from people nearby. Ironically, while many sighted individuals are willing to help, such interactions are infrequent. Asking for help is socially awkward for BLV people, and sighted people lack experience in helping BLV people. Through a mixed-ability research-through-design
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MineXR: Mining Personalized Extended Reality Interfaces arXiv.cs.HC Pub Date : 2024-03-12 Hyunsung Cho, Yukang Yan, Kashyap Todi, Mark Parent, Missie Smith, Tanya R. Jonker, Hrvoje Benko, David Lindlbauer
Extended Reality (XR) interfaces offer engaging user experiences, but their effective design requires a nuanced understanding of user behavior and preferences. This knowledge is challenging to obtain without the widespread adoption of XR devices. We introduce MineXR, a design mining workflow and data analysis platform for collecting and analyzing personalized XR user interaction and experience data
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What would Plato say? Concepts and notions from Greek philosophy applied to gamification mechanics for a meaningful and ethical gamification arXiv.cs.HC Pub Date : 2024-03-12 Kostas Karpouzis
Gamification, the integration of game mechanics in non-game settings, has become increasingly prevalent in various digital platforms; however, its ethical and societal impacts are often overlooked. This paper delves into how Platonic and Aristotelian philosophies can provide a critical framework for understanding and evaluating the ethical dimensions of gamification. Plato's allegory of the cave and
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Fast-Forward Reality: Authoring Error-Free Context-Aware Policies with Real-Time Unit Tests in Extended Reality arXiv.cs.HC Pub Date : 2024-03-12 Xun Qian, Tianyi Wang, Xuhai Xu, Tanya R Jonker, Kashyap Todi
Advances in ubiquitous computing have enabled end-user authoring of context-aware policies (CAPs) that control smart devices based on specific contexts of the user and environment. However, authoring CAPs accurately and avoiding run-time errors is challenging for end-users as it is difficult to foresee CAP behaviors under complex real-world conditions. We propose Fast-Forward Reality, an Extended Reality
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Dynamic Field of View Reduction Related to Subjective Sickness Measures in an HMD-based Data Analysis Task arXiv.cs.HC Pub Date : 2024-03-12 Daniel Zielasko, Alexander Meißner, Sebastian Freitag, Benjamin Weyers, Torsten W. Kuhlen
Various factors influence the degree of cybersickness a user can suffer in an immersive virtual environment, some of which can be controlled without adapting the virtual environment itself. When using HMDs, one example is the size of the field of view. However, the degree to which factors like this can be manipulated without affecting the user negatively in other ways is limited. Another prominent
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Non-discrimination Criteria for Generative Language Models arXiv.cs.HC Pub Date : 2024-03-13 Sara Sterlie, Nina Weng, Aasa Feragen
Within recent years, generative AI, such as large language models, has undergone rapid development. As these models become increasingly available to the public, concerns arise about perpetuating and amplifying harmful biases in applications. Gender stereotypes can be harmful and limiting for the individuals they target, whether they consist of misrepresentation or discrimination. Recognizing gender
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Supporting Annotators with Affordances for Efficiently Labeling Conversational Data arXiv.cs.HC Pub Date : 2024-03-12 Austin Z. Henley, David Piorkowski
Without well-labeled ground truth data, machine learning-based systems would not be as ubiquitous as they are today, but these systems rely on substantial amounts of correctly labeled data. Unfortunately, crowdsourced labeling is time consuming and expensive. To address the concerns of effort and tedium, we designed CAL, a novel interface to aid in data labeling. We made several key design decisions
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Evaluation of Eye Tracking Signal Quality for Virtual Reality Applications: A Case Study in the Meta Quest Pro arXiv.cs.HC Pub Date : 2024-03-11 Samantha Aziz, Dillon J Lohr, Lee Friedman, Oleg Komogortsev
We present an extensive, in-depth analysis of the eye tracking capabilities of the Meta Quest Pro virtual reality headset using a dataset of eye movement recordings collected from 78 participants. In addition to presenting classical signal quality metrics--spatial accuracy, spatial precision and linearity--in ideal settings, we also study the impact of background luminance and headset slippage on device
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Am I the Odd One? Exploring (In)Congruencies in the Realism of Avatars and Virtual Others in Virtual Reality arXiv.cs.HC Pub Date : 2024-03-11 David Mal, Nina Döllinger, Erik Wolf, Stephan Wenninger, Mario Botsch, Carolin Wienrich, Marc Erich Latoschik
Virtual humans play a pivotal role in social virtual environments, shaping users' VR experiences. The diversity in available options and users' preferences can result in a heterogeneous mix of appearances among a group of virtual humans. The resulting variety in higher-order anthropomorphic and realistic cues introduces multiple (in)congruencies, eventually impacting the plausibility of the experience
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Designing Wearable Augmented Reality Concepts to Support Scalability in Autonomous Vehicle-Pedestrian Interaction arXiv.cs.HC Pub Date : 2024-03-08 Tram Thi Minh Tran, Callum Parker, Yiyuan Wang, Martin Tomitsch
Wearable augmented reality (AR) offers new ways for supporting the interaction between autonomous vehicles (AVs) and pedestrians due to its ability to integrate timely and contextually relevant data into the user's field of view. This article presents novel wearable AR concepts that assist crossing pedestrians in multi-vehicle scenarios where several AVs frequent the road from both directions. Three
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A Study on Domain Generalization for Failure Detection through Human Reactions in HRI arXiv.cs.HC Pub Date : 2024-03-10 Maria Teresa Parreira, Sukruth Gowdru Lingaraju, Adolfo Ramirez-Aristizabal, Manaswi Saha, Michael Kuniavsky, Wendy Ju
Machine learning models are commonly tested in-distribution (same dataset); performance almost always drops in out-of-distribution settings. For HRI research, the goal is often to develop generalized models. This makes domain generalization - retaining performance in different settings - a critical issue. In this study, we present a concise analysis of domain generalization in failure detection models
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Design and Development of a Multi-Purpose Collaborative Remote Laboratory Platform arXiv.cs.HC Pub Date : 2024-03-10 Sven Jacobs, Timo Hardebusch, Esther Franke, Henning Peters, Rashed Al Amin, Veit Wiese, Steffen Jaschke
This work-in-progress paper presents the current development of a new collaborative remote laboratory platform. The results are intended to serve as a foundation for future research on collaborative work in remote laboratories. Our platform, standing out with its adaptive and collaborative capabilities, integrates a distributed web-application for streamlined management and engagement in diverse remote
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Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs! arXiv.cs.HC Pub Date : 2024-03-10 Huanqi Yang, Sijie Ji, Rucheng Wu, Weitao Xu
There is a burgeoning discussion around the capabilities of Large Language Models (LLMs) in acting as fundamental components that can be seamlessly incorporated into Artificial Intelligence of Things (AIoT) to interpret complex trajectories. This study introduces LLMTrack, a model that illustrates how LLMs can be leveraged for Zero-Shot Trajectory Recognition by employing a novel single-prompt technique
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Mind Meets Robots: A Review of EEG-Based Brain-Robot Interaction Systems arXiv.cs.HC Pub Date : 2024-03-10 Yuchong Zhang, Nona Rajabi, Farzaneh Taleb, Andrii Matviienko, Yong Ma, Mårten Björkman, Danica Kragic
Brain-robot interaction (BRI) empowers individuals to control (semi-)automated machines through their brain activity, either passively or actively. In the past decade, BRI systems have achieved remarkable success, predominantly harnessing electroencephalogram (EEG) signals as the central component. This paper offers an up-to-date and exhaustive examination of 87 curated studies published during the
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Reframe Anything: LLM Agent for Open World Video Reframing arXiv.cs.HC Pub Date : 2024-03-10 Jiawang Cao, Yongliang Wu, Weiheng Chi, Wenbo Zhu, Ziyue Su, Jay Wu
The proliferation of mobile devices and social media has revolutionized content dissemination, with short-form video becoming increasingly prevalent. This shift has introduced the challenge of video reframing to fit various screen aspect ratios, a process that highlights the most compelling parts of a video. Traditionally, video reframing is a manual, time-consuming task requiring professional expertise
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PAPER-HILT: Personalized and Adaptive Privacy-Aware Early-Exit for Reinforcement Learning in Human-in-the-Loop Systems arXiv.cs.HC Pub Date : 2024-03-09 Mojtaba Taherisadr, Salma Elmalaki
Reinforcement Learning (RL) has increasingly become a preferred method over traditional rule-based systems in diverse human-in-the-loop (HITL) applications due to its adaptability to the dynamic nature of human interactions. However, integrating RL in such settings raises significant privacy concerns, as it might inadvertently expose sensitive user information. Addressing this, our paper focuses on
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A Framework for Effective AI Recommendations in Cyber-Physical-Human Systems arXiv.cs.HC Pub Date : 2024-03-08 Aditya Dave, Heeseung Bang, Andreas A. Malikopoulos
Many cyber-physical-human systems (CPHS) involve a human decision-maker who may receive recommendations from an artificial intelligence (AI) platform while holding the ultimate responsibility of making decisions. In such CPHS applications, the human decision-maker may depart from an optimal recommended decision and instead implement a different one for various reasons. In this letter, we develop a
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Are Large Language Models Aligned with People's Social Intuitions for Human-Robot Interactions? arXiv.cs.HC Pub Date : 2024-03-08 Lennart Wachowiak, Andrew Coles, Oya Celiktutan, Gerard Canal
Large language models (LLMs) are increasingly used in robotics, especially for high-level action planning. Meanwhile, many robotics applications involve human supervisors or collaborators. Hence, it is crucial for LLMs to generate socially acceptable actions that align with people's preferences and values. In this work, we test whether LLMs capture people's intuitions about behavior judgments and communication
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Enabling Developers, Protecting Users: Investigating Harassment and Safety in VR arXiv.cs.HC Pub Date : 2024-03-08 Abhinaya S. B., Aafaq Sabir, Anupam Das
Virtual Reality (VR) has witnessed a rising issue of harassment, prompting the integration of safety controls like muting and blocking in VR applications. However, the lack of standardized safety measures across VR applications hinders their universal effectiveness, especially across contexts like socializing, gaming, and streaming. While prior research has studied safety controls in social VR applications
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Comparison of Spatial Visualization Techniques for Radiation in Augmented Reality arXiv.cs.HC Pub Date : 2024-03-08 Fintan McGee, Roderick McCall, Joan Baixauli
Augmented Reality (AR) provides a safe and low-cost option for hazardous safety training that allows for the visualization of aspects that may be invisible, such as radiation. Effectively visually communicating such threats in the environment around the user is not straightforward. This work describes visually encoding radiation using the spatial awareness mesh of an AR Head Mounted Display. We leverage
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Direction of slip modulates the perception of slip distance and slip speed arXiv.cs.HC Pub Date : 2024-03-08 Ayesha Tooba Khan, Deepak Joshi, Biswarup Mukherjee
Purpose: The purpose of this study was to investigate the psychophysical understanding of the slip stimulus. We emphasized that the perception of slip and its characteristics, such as slip distance and slip speed depend on the interaction between slip direction, slip distance as well as slip speed. Methods: We developed a novel slip induction device to simulate the artificial sense of slip. We conducted
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Sparse Wearable Sonomyography Sensor-based Proprioceptive Proportional Control Across Multiple Gestures arXiv.cs.HC Pub Date : 2024-03-08 Anne Tryphosa Kamatham, Kavita Sharma, Srikumar Venkataraman, Biswarup Mukherjee
Sonomyography (SMG) is a non-invasive technique that uses ultrasound imaging to detect the dynamic activity of muscles. Wearable SMG systems have recently gained popularity due to their potential as human-computer interfaces for their superior performance compared to conventional methods. This paper demonstrates real-time positional proportional control of multiple gestures using a multiplexed 8-channel
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To Reach the Unreachable: Exploring the Potential of VR Hand Redirection for Upper Limb Rehabilitation arXiv.cs.HC Pub Date : 2024-03-08 Peixuan Xiong, Yukai Zhang, Nandi Zhang, Shihan Fu, Xin Li, Yadan Zheng, Jinni Zhou, Xiquan Hu, Mingming Fan
Rehabilitation therapies are widely employed to assist people with motor impairments in regaining control over their affected body parts. Nevertheless, factors such as fatigue and low self-efficacy can hinder patient compliance during extensive rehabilitation processes. Utilizing hand redirection in virtual reality (VR) enables patients to accomplish seemingly more challenging tasks, thereby bolstering
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Trust Recognition in Human-Robot Cooperation Using EEG arXiv.cs.HC Pub Date : 2024-03-08 Caiyue Xu, Changming Zhang, Yanmin Zhou, Zhipeng Wang, Ping Lu, Bin He
Collaboration between humans and robots is becoming increasingly crucial in our daily life. In order to accomplish efficient cooperation, trust recognition is vital, empowering robots to predict human behaviors and make trust-aware decisions. Consequently, there is an urgent need for a generalized approach to recognize human-robot trust. This study addresses this need by introducing an EEG-based method
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AQuA: Automated Question-Answering in Software Tutorial Videos with Visual Anchors arXiv.cs.HC Pub Date : 2024-03-08 Saelyne Yang, Jo Vermeulen, George Fitzmaurice, Justin Matejka
Tutorial videos are a popular help source for learning feature-rich software. However, getting quick answers to questions about tutorial videos is difficult. We present an automated approach for responding to tutorial questions. By analyzing 633 questions found in 5,944 video comments, we identified different question types and observed that users frequently described parts of the video in questions
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MarkupLens: An AI-Powered Tool to Support Designers in Video-Based Analysis at Scale arXiv.cs.HC Pub Date : 2024-03-08 Tianhao He, Ying Zhang, Evangelos Niforatos, Gerd Kortuem
Video-Based Design (VBD) is a design methodology that utilizes video as a primary tool for understanding user interactions, prototyping, and conducting research to enhance the design process. Artificial Intelligence (AI) can be instrumental in video-based design by analyzing and interpreting visual data from videos to enhance user interaction, automate design processes, and improve product functionality
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ViboPneumo: A Vibratory-Pneumatic Finger-Worn Haptic Device for Altering Perceived Texture Roughness in Mixed Reality arXiv.cs.HC Pub Date : 2024-03-08 Shaoyu Cai, Zhenlin Chen, Haichen Gao, Ya Huang, Qi Zhang, Xinge Yu, Kening Zhu
Extensive research has been done in haptic feedback for texture simulation in virtual reality (VR). However, it is challenging to modify the perceived tactile texture of existing physical objects which usually serve as anchors for virtual objects in mixed reality (MR). In this paper, we present ViboPneumo, a finger-worn haptic device that uses vibratory-pneumatic feedback to modulate (i.e., increase
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Putting Language into Context Using Smartphone-Based Keyboard Logging arXiv.cs.HC Pub Date : 2024-03-08 Florian Bemmann, Timo Koch, Maximilian Bergmann, Clemens Stachl, Daniel Buschek, Ramona Schoedel, Sven Mayer
While the study of language as typed on smartphones offers valuable insights, existing data collection methods often fall short in providing contextual information and ensuring user privacy. We present a privacy-respectful approach - context-enriched keyboard logging - that allows for the extraction of contextual information on the user's input motive, which is meaningful for linguistics, psychology
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How Culture Shapes What People Want From AI arXiv.cs.HC Pub Date : 2024-03-08 Xiao Ge, Chunchen Xu, Daigo Misaki, Hazel Rose Markus, Jeanne L Tsai
There is an urgent need to incorporate the perspectives of culturally diverse groups into AI developments. We present a novel conceptual framework for research that aims to expand, reimagine, and reground mainstream visions of AI using independent and interdependent cultural models of the self and the environment. Two survey studies support this framework and provide preliminary evidence that people