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arXiv 2025年

作者： Ran, Zihe Fan, Xianzhe Li, Xiyu Li, Franklin Mingzhe Lu, Zhicong Xiao, Qing Wang, Yanyun Communication University of China Beijing China Tsinghua University Beijing China Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States Department of Computer Science George Mason University FairfaxVA United States College of Media Communication and Information University of Colorado Boulder BoulderCO United States

As blind and low-vision (BLV) players engage more deeply with games, accessibility features have become essential. While some research has explored tools and strategies to enhance game accessibility, the specific experiences of these players with mobile games remain underexamined. This study addresses this gap by investigating how BLV users experience mobile games with varying accessibility levels. Through interviews with 32 experienced BLV mobile players, we explore their perceptions, challenges, and strategies for engaging with mobile games. Our findings reveal that BLV players turn to mobile games to alleviate boredom, achieve a sense of accomplishment, and build social connections, but face barriers depending on the game’s accessibility level. We also compare mobile games to other forms of gaming, highlighting the relative advantages of mobile games, such as the inherent accessibility of smartphones. This study contributes to understanding BLV mobile gaming experiences and provides insights for enhancing accessible mobile game design. Copyright © 2025, The Authors. All rights reserved.

关键词： Game design

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Global and Transdisciplinary Perspectives on Dark Patterns and Deceptive Design Practice

Global and Transdisciplinary Perspectives on Dark Patterns a...

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2025 CHI Conference on human Factors in Computing Systems, CHI EA 2025

作者： Seaborn, Katie Gray, Colin M. Gunawan, Johanna Mildner, Thomas Schäfer, René Chamorro, Lorena Sanchez Nakamura, Satoshi Department of Industrial Engineering and Economics Institute of Science Tokyo Tokyo Japan UXP2 Lab. Indiana University BloomingtonIN United States Law and Tech Lab. Maastricht University Maastricht Netherlands University of Bremen Bremen Germany RWTH Aachen University Aachen Germany Human-Computer Interaction Research Group University of Luxembourg Esch-Sur-Alzette Luxembourg Meiji University School of Interdisciplinary Mathematical Sciences Nakano Tokyo Japan

ISBN: (纸本)9798400713958

Dark patterns and deceptive designs (DPs) refer to user interfaces (UIs) that trick people into interactions that benefit the service providers. Today, academic research, legal action, and media coverage has raised awareness among a diversity of stakeholders worldwide. Yet, the lens has focused on Western and English contexts. We propose a Special Interest group (SIG) that centres on cross-cultural and interdisciplinary engagement. The organizing team, who hail from a plurality of nations and disciplines, will spark discussion by sharing their knowledge—findings, frameworks, methods, and tools—and culturally-sensitive perspectives on deception in modern digital products and services. Attendees will participate in a small group drawing activity, whereby culturally-specific DPs and disciplinary perspectives can be surfaced and communicated without reliance on a specific language or cultural frame. This SIG is expected to draw in a diversity of designers, researchers, security experts, and legal scholars concerned about ethical design practice. © 2025 Copyright held by the owner/author(s).

关键词： User profile

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AnyTSR: Any-Scale Thermal Super-Resolution for UAV

arXiv

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arXiv 2025年

作者： Li, Mengyuan Fu, Changhong Lu, Ziyu Zhang, Zijie Zuo, Haobo Yao, Liangliang School of Mechanical Engineering Tongji University Shanghai201804 China Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Tongji University Shanghai201804 China Department of Computer Science University of Hong Kong Hong Kong999077 Hong Kong

Thermal imaging can greatly enhance the application of intelligent unmanned aerial vehicles (UAV) in challenging environments. However, the inherent low resolution of thermal sensors leads to insufficient details and blurred boundaries. Super-resolution (SR) offers a promising solution to address this issue, while most existing SR methods are designed for fixed-scale SR. They are computationally expensive and inflexible in practical applications. To address above issues, this work proposes a novel any-scale thermal SR method (AnyTSR) for UAV within a single model. Specifically, a new image encoder is proposed to explicitly assign specific feature code to enable more accurate and flexible representation. Additionally, by effectively embedding coordinate offset information into the local feature ensemble, an innovative any-scale upsampler is proposed to better understand spatial relationships and reduce artifacts. Moreover, a novel dataset (UAV-TSR), covering both land and water scenes, is constructed for thermal SR tasks. Experimental results demonstrate that the proposed method consistently outperforms state-of-the-art methods across all scaling factors as well as generates more accurate and detailed high-resolution images. The code is located at https:// ***/vision4robotics/AnyTSR. Copyright © 2025, The Authors. All rights reserved.

关键词： Drones

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Evaluating the Benefits of the Immersive Space to Think

Evaluating the Benefits of the Immersive Space to Think

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2020 IEEE Conference on Virtual Reality and 3D User Interfaces, VRW 2020

作者： Lisle, Lee Chen, Xiaoyu Edward Gitre, J.K. North, Chris Bowman, Doug A. Center for Human-Computer Interaction Department of Computer Science Virginia Tech United States Virginia Tech Grado Department of Industrial and Systems Engineering United States Center for Human-Computer Interaction Department of History Virginia Tech United States

ISBN: (纸本)9781728165325

Sensemaking with large multimedia dataset is a cognitively intensive task that requires analysts to understand the underlying stories that the dataset tells. Often, analysts use tools in order to offload cognition as well as convey their new understanding of the dataset;however, existing tools are limited by their underlying technologies. We have proposed a novel virtual reality tool to support sensemaking called the Immersive Space to Think (IST). IST can aid the process of analyzing multimedia data, but it remains unproven whether IST improves sensemaking performance over a traditional desktop setting. In a study performed over six weeks, one participant used both IST and traditional methods of sensemaking with a dataset of 100 text documents of transcribed survey responses from World War 2 soldiers to perform historical analysis. The participant was asked guided questions that produced three essays with their understanding of the data. After conducting a blind evaluation of the participant's interpretation of the data, a team of three experts in historical analysis concluded that the essays written with IST displayed a better understanding of the dataset. Furthermore, the participant gave positive feedback on IST, and also suggested possible improvements. © 2020 IEEE.

关键词： Surveys

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Virtual Reality for Health and Wellbeing 22

Virtual Reality for Health and Wellbeing

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21st International Conference on Mobile and Ubiquitous Multimedia, MUM 2022

作者： Ferreira-Brito, Filipa Gjoreski, Hristijan Mayora, Oscar Luštrek, Mitja Kizhevska, Emilija Guerreiro, João Gerling, Kathrin Bermúdez I Badia, Sergi Guerreiro, Tiago LASIGE Faculdade de Ciências da Universidade de Lisboa Portugal Ss. Cyril and Methodius University in Skopje Skopje Macedonia Center for Health and Wellbeing Fondazione Bruno Kessler Trento Italy Department of Intelligent Systems Jožef Stefan Institute Slovenia Slovenia Ss. Cyril and Methodius University in Skopje Macedonia KU Leuven Department of Computer Science Human-Computer Interaction Belgium Departamento de Engenharia Informatica and NOVA Laboratory for Computer Science and Informatics Universidade da Madeira Portugal and ARDITI Portugal

ISBN: (纸本)9781450398213

Virtual Reality (VR) has become a mainstream opportunity to develop immersive environments where people are exposed to relevant stimuli in a systematic but safe way. Besides the controlled exposure to stimuli, VR systems enable a more efficient and unbiased gathering of information with practical applications in diagnosis, intervention, and health monitoring processes. Nonetheless, scientific literature has demonstrated that interacting with VR technology and its peripherals can be challenging, especially in populations less familiar with technology (e.g., older adults) or with clinical conditions that are not adequately accommodated by the technology, such as cognitive (e.g., dementia) or physical impairments (e.g., blindness). This workshop will focus on systems, technological approaches, and theoretical frameworks to develop user/patient-centred VR tools for diagnosis, intervention, and monitoring of health and wellbeing outcomes. Moreover, we welcome work focused on accessibility issues, aiming to promote equal access and opportunity to use VR tools by people with diverse abilities. © 2022 ACM.

关键词： Virtual reality

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Investigation on data adaptation techniques for neural named entity recognition 59

Investigation on data adaptation techniques for neural named...

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2021 Student Research Workshop, SRW 2021 at the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021

作者： Tokarchuk, Evgeniia Thulke, David Wang, Weiyue Dugast, Christian Ney, Hermann Informatics Institute University of Amsterdam Netherlands Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University Germany

ISBN: (纸本)9781954085558

Data processing is an important step in various natural language processing tasks. As the commonly used datasets in named entity recognition contain only a limited number of samples, it is important to obtain additional labeled data in an efficient and reliable manner. A common practice is to utilize large monolingual unlabeled corpora. Another popular technique is to create synthetic data from the original labeled data (data augmentation). In this work, we investigate the impact of these two methods on the performance of three different named entity recognition tasks. © 2021 Association for Computational Linguistics.

关键词： Data handling

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Revisiting Checkpoint Averaging for Neural Machine Translation

arXiv

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arXiv 2022年

作者： Gao, Yingbo Herold, Christian Yang, Zijian Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University Germany

Checkpoint averaging is a simple and effective method to boost the performance of converged neural machine translation models. The calculation is cheap to perform and the fact that the translation improvement almost comes for free, makes it widely adopted in neural machine translation research. Despite the popularity, the method itself simply takes the mean of the model parameters from several checkpoints, the selection of which is mostly based on empirical recipes without many justifications. In this work, we revisit the concept of checkpoint averaging and consider several extensions. Specifically, we experiment with ideas such as using different checkpoint selection strategies, calculating weighted average instead of simple mean, making use of gradient information and fine-tuning the interpolation weights on development data. Our results confirm the necessity of applying checkpoint averaging for optimal performance, but also suggest that the landscape between the converged checkpoints is rather flat and not much further improvement compared to simple averaging is to be obtained. Copyright © 2022, The Authors. All rights reserved.

关键词： Neural machine translation

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Let's Influence Algorithms Together: How Millions of Fans Build Collective Understanding of Algorithms and Organize Coordinated Algorithmic Actions

arXiv

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arXiv 2024年

作者： Xiao, Qing Zheng, Yuhang Fan, Xianzhe Zhang, Bingbing Lu, Zhicong Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States University of Amsterdam Amsterdam Netherlands Tsinghua University Beijing China School of Journalism and Mass Communication University of Iowa Iowa CityIA United States Department of Computer Science George Mason University FairfaxVA United States

Previous research pays attention to how users strategically understand and consciously interact with algorithms but mainly focuses on an individual level, making it difficult to explore how users within communities could develop a collective understanding of algorithms and organize collective algorithmic actions. Through a two-year ethnography of online fan activities, this study investigates 43 core fans who always organize large-scale fans collective actions and their corresponding general fan groups. This study aims to reveal how these core fans mobilize millions of general fans through collective algorithmic actions. These core fans reported the rhetorical strategies used to persuade general fans, the steps taken to build a collective understanding of algorithms, and the collaborative processes that adapt collective actions across platforms and cultures. Our findings highlight the key factors that enable computer-supported collective algorithmic actions and extend collective action research into the large-scale domain targeting algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Consensus algorithm

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Structural and functional neural correlates of sensorimotor deficits in progression of hepatic encephalopathy

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Magnetic Resonance Letters 2025年 6-16页

作者： Guanchen Sha Yuefan Liu Yutong Cao Qi Zhang Yining Zhang Yuanyuan Chen Qiuyun Fan Yue Cheng Department of Biomedical Engineering College of Precision Instruments and Optoelectronics Engineering Tianjin University Tianjin Key Laboratory of Brain Science and Neuroengineering Academy of Medical Engineering and Translational Medicine Tianjin University Department of Medical Imaging Tianjin First Central Hospital Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration State Key Laboratory of Advanced Medical Materials and Devices

Hepatic encephalopathy(HE) is a neurological condition that occurs as a complication of liver dysfunction that involves sensorimotor symptoms in addition to cognitive and behavioral changes, particularly in cases of severe liver disease or cirrhosis. Previous studies have reported spatially distributed structural and functional abnormalities related to HE, but the exact relationship between the structural and functional alterations with respect to disease progression remains unclear. In this study, we performed surface-based cortical thickness comparisons and functional connectivity(FC) analyses between three cross-sectional groups: healthy controls(HC, N = 51), patients with minimal hepatic encephalopathy(MHE, N = 50), patients with overt hepatic encephalopathy(OHE, N = 51). In addition to the distributed cortical thinning that is extensively thought to be associated with cognitive decline in HE, we found significant cortical thickening in the left parahippocampal gyrus cortex in the OHE group(p < 0.001, p = 0.009) as compared to the HC and MHE group respectively, which is further corroborated by the significant correlation between the cortical thickness and digit symbol test(DST) scores. Furthermore, the decreased FC between the right postcentral gyrus and several sensory regions(bilateral somatosensory and visual cortices) was found to be significant in MHE patients as compared to the HC group. Our results revealed cross-sectional structural and functional variations concerning disease progression across different subsystems(e.g., visual, motor and sensory), providing evidence that can potentially explain the mechanisms underlying the sensorimotor and cognitive deficits related to HE.

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What Makes Im Users (Un)Responsive: An Empirical Investigation for Understanding Im Responsiveness

SSRN

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SSRN 2022年

作者： Lee, Hao-Ping 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, The Authors. All rights reserved.

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