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IEEE International Symposium on Mixed and Augmented Reality Workshops (ISMARW)

作者： Ke Li Tim Rolff Reinhard Bacher Frank Steinicke Deutsches Elektronen-Synchrotron DESY Germany Department of Informatics Human-Computer Interaction Universität Hamburg Department of Informatics Computer Vision Universität Hamburg

Multi-user collaboration at research and development (R&D) workbenches in advanced optics laboratories involves updating and documenting the status of hundreds of components. Although there are abundant mixed reality (MR) systems to support the collaboration of spatially co-located users, limited methods are available to facilitate cooperation in the spatial-temporal domain. Inspired by the version control workflow used in software development, we propose RealityGit, a novel cross-reality (CR) system design that leverages the recent advancements of neural radiance fields (NeRF). We illustrate how the NeRF model can be used to channel users with different extended reality (XR) experiences by providing an accurate immersive visual documentation of the historical states of a complex R&D workbench. We demonstrate the feasibility of such a system through an implementation where users could contribute to the version control workflows by integrating historical NeRF scans into their MR devices or providing status reviews by annotating or editing a NeRF model in virtual reality (VR).

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Emotion Recognition Method Based on EEG Signals: 4D-CapsBLnet Model Integrating Spatio-Temporal Features 2

Emotion Recognition Method Based on EEG Signals: 4D-CapsBLne...

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2nd IEEE International Conference on Control, Electronics and computer Technology, ICCECT 2024

作者： Zhuang, Chenze Dai, Licao Fu, Qiang College of Computer Science University of South China Hengyang421001 China Human Factor Institute University of South China Hengyang421001 China University of South China Department of Management Science and Engineering Hengyang421001 China

ISBN: (纸本)9798350380958

Emotion recognition technology based on electroencephalogram (EEG) signals has become a focal point for experts and scholars globally. To improve the accuracy of machine understanding of human emotions, this paper characterizes the multidimensional information features in EEG signals, and solves the problem of 4-dimensional fusion of temporal, frequency and 2D spatial features of EEG signals, and we present a novel method named 4D-CapsBLnet. First, we transformed the multidimensional features from various channels into 4D structures for training the deep learning model. Second, we utilized Capsule Networks (CapsNet) to capture spatial and frequency information from each temporal slice of 4D inputs, while Bidirectional Long Short- Term Memory Networks (Bi-LSTM) was employed to capture temporal dependencies. To comprehensively assess the model's performance, we conducted a five-fold cross-validation with a maximum epoch limit and early stopping strategy. The average accuracy and standard deviation on the SEED, SEED-IV, and SEED-V datasets are 95.06% ± 1.65%, 88.47% ± 1.74%, and 88.23% ± 1.12%, respectively. Compared to similar research methods, the proposed model in this paper demonstrates robustness and superior performance in emotion recognition tasks. © 2024 IEEE.

关键词： Emotion Recognition

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Effects of Point Size and Opacity Adjustments in Scaterplots

Effects of Point Size and Opacity Adjustments in Scaterplots

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2024 CHI Conference on human Factors in Computing Sytems, CHI 2024

作者： Strain, Gabriel Stewart, Andrew J. Warren, Paul Jay, Caroline Department of Computer Science Faculty of Science and Engineering University of Manchester Manchester United Kingdom Division of Psychology Communication and Human Neuroscience School of Health Sciences Faculty of Biology Medicine and Health University of Manchester Manchester United Kingdom

ISBN: (纸本)9798400703300

Systematically changing the size and opacity of points on scatterplots can be used to induce more accurate perceptions of correlation by viewers. Evidence points to the mechanisms behind these effects being similar, so one may expect their combination to be additive regarding their effects on correlation estimation. We present a fully-reproducible study in which we combine techniques for influencing correlation perception to show that in reality, effects of changing point size and opacity interact in a non-additive fashion. We show that there is a great deal of scope for using visual features to change viewers' perceptions of data visualizations. Additionally, we use our results to further interrogate the perceptual mechanisms at play when changing point size and opacity in scatterplots. © 2024 Copyright held by the owner/author(s)

关键词： Opacity

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What makes IM users (un)responsive: An empirical investigation for understanding IM responsiveness

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International Journal of human computer Studies 2023年 172卷

作者： Lee, Hao-Ping [Hank] Chiang, Yi-Shyuan Chou, Yu-Ling Lin, Kung-Pai Chang, Yung-Ju Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Human–Computer Interaction Institute Carnegie Mellon University PittsburghPA United States Department of Computer Science University of Illinois Urbana-Champaign UrbanaIL United States

Instant messaging (IM) communication has been widely studied due to its prevalence in our everyday communication. Numerous factors that contribute to (un)responsiveness have been identified. Yet an integrated view of the factors that influence IM responsiveness remains absent. This paper reports qualitative findings from interviews with 46 IM users, and identifies five main elements underlying IM users’ response decisions: response habits, need fulfillment, perceived obligation, perceived readiness/suitability, and pace/rhythm coordination. To the best of our knowledge, this is the first integrated view of the key elements underlying IM responsiveness. Among these elements, we particularly highlight that regarding the influence of contextual factors on IM responsiveness, what may matters more is IM users’ perceptions of their readiness and suitability of the contexts, rather than the contexts’ objective properties. We also uncovered pace/rhythm coordination as a crucial factor behind IM responsiveness, which has been little discussed in the literature. Responsiveness, as our findings show, was often not a consequence, but a manifestation, of users’ pursuit of specific responsiveness-related aims such as ongoing shaping and sustaining of a dyad's pace and rhythm. © 2022 Elsevier Ltd

关键词： Message passing

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"I am a Technology Creator": Black Girls as Technosocial Change Agents in a Culturally-Responsive Robotics Camp 25

"I am a Technology Creator": Black Girls as Technosocial Cha...

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Proceedings of the 2025 CHI Conference on human Factors in Computing Systems

作者： Chun Li Jaemarie Solyst Safiyyah Scott Gabriella Howse Tara Nkrumah Erin Walker Amy Ogan Angela E.B. Stewart Department of Informatics and Networked System University of Pittsburgh Pittsburgh Pennsylvania USA Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh Pennsylvania USA School of Computer Science Carnegie Mellon University Pittsburgh Pennsylvania USA Center for Gender Equity in Science and Technology Arizona State University Tempe Arizona USA Department of Computer Science University of Pittsburgh Pittsburgh Pennsylvania USA

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Are LLMs Aware that Some Questions are not Open-ended?

Are LLMs Aware that Some Questions are not Open-ended?

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Yang, Dongjie Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

ISBN: (纸本)9798891761681

Large Language Models (LLMs) have shown the impressive capability of answering questions in a wide range of scenarios. However, when LLMs face different types of questions, it is worth exploring whether LLMs are aware that some questions have limited answers and need to respond more deterministically but some do not. We refer to this as question awareness of LLMs. The lack of question awareness in LLMs leads to two phenomena that LLMs are: (1) too casual to answer non-open-ended questions or (2) too boring to answer open-ended questions. In this paper, we first evaluate the question awareness in LLMs. The experimental results show that LLMs have the issues of lacking awareness of questions in certain domains, e.g. factual knowledge, resulting in hallucinations during the generation. To mitigate these, we propose a method called Question Awareness Temperature Sampling (QuATS). This method enhances the question awareness of LLMs by adaptively adjusting the output distributions based on question features. The automatic adjustment in QuATS eliminates the need for manual temperature tuning in text generation and consistently improves model performance in various benchmarks. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Opportunities for Serious Game Technologies to Engage Children with Autism in a Pakistani Sociocultural and Institutional Context: An investigation of the design space for serious game technologies to enhance engagement of children with autism and to facilitate external support provided 22

Opportunities for Serious Game Technologies to Engage Childr...

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Proceedings of the 34th Australian Conference on human-computer interaction

作者： Sara Muneeb Laurianne Sitbon Faizan Ahmad Research Center for Human Computer Interaction COMSATS University Islamabad Lahore Campus Pakistan and School of Computer Science Queensland University of Technology (QUT) Australia School of Computer Science Queensland University of Technology (QUT) Australia Department of Computer Science School of Technologies Cardiff Metropolitan University United Kingdom

ISBN: (纸本)9798400700248

Usability and design of serious game technologies have been widely investigated as academic interventions tools for children with autism. However, besides the technology, the sociocultural and institutional context also impacts the gameplay activities of children with autism as well as the external support provided by instructors. Therefore, this paper investigates i) the impact of sociocultural and institutional context over the engagement of children with autism with serious game technologies, ii) the types of external support children with autism are offered or require during gameplay session, and iii) the type of rewards and encouragers that can act as unbiased support to increase the engagement of the children with autism during *** paper investigates these factors with an inductive analysis of educational gameplay activities of 23 children with autism in Lahore, Pakistan. Our study found that sociocultural and institutional context has substantial impact over the gameplay activities of children with autism. Children required both physical and verbal support during the gameplay activities, and institutional context influences the behavior of instructors as well. Finally, dynamic animations, rewards and encouragers can keep the children engaged for longer in the gameplay.

关键词： serious game technologies children with autism Game-based learning support context and encouragers rewards

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Robust Knowledge Distillation from RNN-T Models with Noisy Training Labels Using Full-Sum Loss 48

Robust Knowledge Distillation from RNN-T Models with Noisy T...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zeineldeen, Mohammad Audhkhasi, Kartik Baskar, Murali Karthick Ramabhadran, Bhuvana Rwth Aachen University Human Language Technology and Pattern Recognition Computer Science Department Aachen52074 Germany Google Llc New York United States

ISBN: (纸本)9781728163277

This work studies knowledge distillation (KD) and addresses its constraints for recurrent neural network transducer (RNN-T) models. In hard distillation, a teacher model transcribes large amounts of unlabelled speech to train a student model. Soft distillation is another popular KD method that distills the output logits of the teacher model. Due to the nature of RNN-T alignments, applying soft distillation between RNNT architectures having different posterior distributions is challenging. In addition, bad teachers having high word-error-rate (WER) reduce the efficacy of KD. We investigate how to effectively distill knowledge from variable quality ASR teachers, which has not been studied before to the best of our knowledge. We show that a sequence-level KD, full-sum distillation, outperforms other distillation methods for RNN-T models, especially for bad teachers. We also propose a variant of full-sum distillation that distills the sequence discriminative knowledge of the teacher leading to further improvement in WER. We conduct experiments on public datasets namely SpeechStew and LibriSpeech, and on in-house production data. © 2023 IEEE.

关键词： Recurrent neural networks

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Development and Initial Evaluation of a Digital Phenotype Collection System for Adolescents: Proof-of-Concept Study

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JMIR Formative Research 2024年 8卷 e59623页

作者： Cho, Minseo Park, Doeun Choo, Myounglee Kim, Jinwoo Han, Doug Hyun Human Computer Interaction Lab Department of Cognitive Science Yonsei University Seoul South Korea Human Computer Interaction Lab School of Business Yonsei University Seoul South Korea HAII Corp Seoul South Korea College of Medicine Chung-Ang University Seoul South Korea

Background: The growing concern on adolescent mental health calls for proactive early detection and intervention strategies. There is a recognition of the link between digital phenotypes and mental health, drawing attention to their potential use. However, the process of collecting digital phenotype data presents challenges despite its promising prospects. Objective: This study aims to develop and validate system concepts for collecting adolescent digital phenotypes that effectively manage inherent challenges in the process. Methods: In a formative investigation (N=34), we observed adolescent self-recording behaviors and conducted interviews to develop design goals. These goals were then translated into system concepts, which included planners resembling interfaces, simplified data input with tags, visual reports on behaviors and moods, and supportive ecological momentary assessment (EMA) prompts. A proof-of-concept study was conducted over 2 weeks (n=16), using tools that simulated the concepts to record daily activities and complete EMA surveys. The effectiveness of the system was evaluated through semistructured interviews, supplemented by an analysis of the frequency of records and responses. Results: The interview findings revealed overall satisfaction with the system concepts, emphasizing strong support for self-recording. Participants consistently maintained daily records throughout the study period, with no missing data. They particularly valued the recording procedures that aligned well with their self-recording goal of time management, facilitated by the interface design and simplified recording procedures. Visualizations during recording and subsequent report viewing further enhanced engagement by identifying missing data and encouraging deeper self-reflection. The average EMA compliance reached 72%, attributed to a design that faithfully reflected adolescents’ lives, with surveys scheduled at convenient times and supportive messages tailored to their dai

关键词： adolescent mental health adolescents digital phenotyping ecological momentary assessment phenotype data phenotypes proof of concept qualitative research self-monitoring smartphone apps

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Ethical Issues in Near-Future Socially Supportive Smart Assistants for Older Adults

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2023年第4期4卷 291-301页

作者： London, Alex John Razin, Yosef S. Borenstein, Jason Eslami, Motahhare Perkins, Russell Robinette, Paul Carnegie Mellon University Department of Philosophy PittsburghPA15213 United States Georgia Institute of Technology School of Aerospace Engineering AtlantaGA30332 United States Georgia Institute of Technology School of Public Policy and Office of Graduate Education AtlantaGA30332 United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA15213 United States University of Massachusetts Lowell Department of Electrical and Computer Engineering LowellMA01854 United States

This paper considers novel ethical issues pertaining to near-future artificial intelligence (AI) systems that seek to support, maintain, or enhance the capabilities of older adults as they age and experience cognitive decline. In particular, we focus on smart assistants (SAs) that would seek to provide proactive assistance and mediate social interactions between users and other members of their social or support networks. Such systems would potentially have significant utility for users and their caregivers if they could reduce the cognitive load for tasks that help older adults maintain their autonomy and independence. However, proactively supporting even simple tasks, such as providing the user with a summary of a meeting or a conversation, would require a future SA to engage with ethical aspects of human interactions which computational systems currently have difficulty identifying, tracking, and navigating. If SAs fail to perceive ethically relevant aspects of social interactions, the resulting deficit in moral discernment would threaten important aspects of user autonomy and well-being. After describing the dynamic that generates these ethical challenges, we note how simple strategies for prompting user oversight of such systems might also undermine their utility. We conclude by considering how near-future SAs could exacerbate current worries about privacy, commodification of users, trust calibration and injustice. © 2020 IEEE.

关键词： Cognitive systems

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