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

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

ISBN: (纸本)9798400713941

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. © 2025 Copyright held by the owner/author(s).

关键词： Blind and Low-Vision (BLV) Users Game Accessibility Global South Mobile Accessibility Mobile Game

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Let's Influence Algorithms Together: How Millions of Fans Build Collective Understanding of Algorithms and Organize Coordinated Algorithmic Actions 25

Let's Influence Algorithms Together: How Millions of Fans Bu...

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

作者： Xiao, Qing Zheng, Yuhang Fan, Xianzhe Zhang, Bingbing Lu, Zhicong Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States University of Amsterdam Amsterdam Amsterdam Netherlands Tsinghua University Beijing China School of Journalism and Mass Communication University of Iowa iowa City IA United States Department of Computer Science George Mason University Fairfax VA United States

ISBN: (纸本)9798400713941

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. © 2025 Copyright held by the owner/author(s).

关键词： Algorithm Collective Algorithmic Action Collective Understanding of Algorithm Fandom Studies Folk Theory of Algorithm

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The Mobile Office: A Mobile AR Systems for Productivity Applications in Industrial Environments 13th

The Mobile Office: A Mobile AR Systems for Productivity Appl...

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13th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2021, Held as Part of the 23rd HCI International Conference, HCII 2021

作者： Linares Garcia, Daniel Antonio Dongre, Poorvesh Roofigari-Esfahan, Nazila Bowman, Doug A. Department of Building Construction Virginia Tech BlacksburgVA24060 United States Department of Computer Science Virginia Tech BlacksburgVA24060 United States Center for Human-Computer Interaction Virginia Tech BlacksburgVA24060 United States

ISBN: (纸本)9783030775988

This article proposes the Mobile Office, an AR-Based System for productivity applications in industrial environments. It focuses on addressing workers’ needs while mobilizing in complex environments and when workers want to do productive work similar to a workstation setting. For this purpose, the Mobile Office relies on a bi-modal approach (mobile and static modes) to addresses both scenarios while considering critical aspects such as UI, ergonomics, interaction, safety, and cognitive user abilities. Its development relies first on a systematic literature review for establishing guidelines and system aspects. Then AR-UI mockups are presented to incorporate literature and authors’ expertise in this area. Three hardware configurations are also presented for the implementation of the Mobile Office. Validation of the Mobile Office was made through a survey to potential users that provided their feedback about their perceptions of proposed system. The survey results revealed concordance of critical aspects of particular importance for effective productivity support on the Mobile Office’s focus scenarios. We incorporated these critical aspects and suggested future research direction for the Mobile Office’s further development and significance. © 2021, Springer Nature Switzerland AG.

关键词： Augmented reality

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Mechanical Design with Experimental Verification of a Lightweight Exoskeleton Chair

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Journal of Bionic Engineering 2021年第2期18卷 319-332页

作者： Zihao Du Zefeng Yan Tiantian Huang Ou Bai Qin Huang Bin Han State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Human Cyber-Physical Systems Laboratory Department of Electrical and Computer EngineeringFlorida International UniversityMiami 33174USA Department of Rehabilitation Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China

In this study,a human-chair model was developed as the basis for a wearable-chair design.A prototype chair,HUST-EC,based on the model was fabricated and *** the optimization under the golden divisional method,an optimized simulation of the operating mode with the lowest chair height was implemented.A novel multi-link support structure has been established with parameters optimized using Matlab *** stress analysis of the solid models was conducted to ensure the adequate support from the designed chair for the *** subjects participated in the evaluation experiment,who performed both static tasks and dynamic *** experimental results consisted of subjective evaluation and objective *** experimental data demonstrate that(1)the HUST-EC can effectively reduce the activation level of related muscles at a variety of tasks;(2)the plantar pressure was reduced by 54%–67%;(3)the angle between the upper body and the vertical axis was reduced by 59%–77%;(4)the subjective scores for chair comfortability,portability,and stability were all higher than *** results further revealed that the designed chair can reduce the musculoskeletal burden and may improve work efficiency.

关键词： exoskeleton wearable chair bionic robot mechanism design ergonomics

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How Users Who are Blind or Low Vision Play Mobile Games: Perceptions, Challenges, and Strategies

arXiv

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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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Somatic Mutations and Alzheimer's Disease

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JOURNAL OF ALZHEIMERS DISEASE 2022年第2期90卷 475-493页

作者： [Anonymous] [a] Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong China [b] Department of Computer Science and Technology University of Cambridge UK [c] The Elton Laboratory for Molecular Neuroendocrinology Department of Human Molecular Genetics and Biochemistry Sackler Faculty of Medicine Adams Super Center for Brain Studies and Sagol School of Neuroscience Tel Aviv University Tel Aviv Israel

Alzheimer's disease (AD) represents a global health challenge, with an estimated 55 million people suffering from the non-curable disease across the world. While amyloid-beta plaques and tau neurofibrillary tangles in the brain define AD proteinopathy, it has become evident that diverse coding and non-coding regions of the genome may significantly contribute to AD neurodegeneration. The diversity of factors associated with AD pathogenesis, coupled with age-associated damage, suggests that a series of triggering events may be required to initiate AD. Since somatic mutations accumulate with aging, and aging is a major risk factor for AD, there is a great potential for somatic mutational events to drive disease. Indeed, recent data from the Gozes team/laboratories as well as other leading laboratories correlated the accumulation of somatic brain mutations with the progression of tauopathy. In this review, we lay the current perspectives on the principal genetic factors associated with AD and the potential causes, highlighting the contribution of somatic mutations to the pathogenesis of late onset Alzheimer's disease. The roles that artificial intelligence and big data can play in accelerating the progress of causal somatic mutation markers/biomarkers identification, and the associated drug discovery/repurposing, have been highlighted for future AD and other neurodegenerations, with the aim to bring hope for the vulnerable aging population.

关键词： Alzheimer's disease amyloid-beta peptide artificial intelligence big data late onset Alzheimer's disease somatic mutations tau

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Neural P3M: A Long-Range interaction Modeling Enhancer for Geometric GNNs 38

Neural P3M: A Long-Range Interaction Modeling Enhancer for G...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wang, Yusong Cheng, Chaoran Li, Shaoning Ren, Yuxuan Shao, Bin Liu, Ge Heng, Pheng-Ann Zheng, Nanning National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China University of Illinois Urbana-Champaign United States Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong University of Science and Technology of China China Microsoft Research AI4Science United States

Geometric graph neural networks (GNNs) have emerged as powerful tools for modeling molecular geometry. However, they encounter limitations in effectively capturing long-range interactions in large molecular systems due to the localization assumption of GNN. To address this challenge, we introduce Neural P3M, a versatile enhancer of geometric GNNs to expand the scope of their capabilities by incorporating mesh points alongside atoms and reimaging traditional mathematical operations in a trainable manner. Neural P3M exhibits flexibility across a wide range of molecular systems and demonstrates remarkable accuracy in predicting energies and forces, outperforming on benchmarks such as the MD22 dataset. It also achieves an average improvement of 22% on the OE62 dataset while integrating with various architectures. Codes are available at https://***/OnlyLoveKFC/Neural_P3M. © 2024 Neural information processing systems foundation. All rights reserved.

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Chinese Spelling Correction as Rephrasing Language Model

arXiv

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arXiv 2023年

作者： Liu, Linfeng Wu, Hongqiu 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 China

This paper studies Chinese Spelling Correction (CSC), which aims to detect and correct the potential spelling errors in a given sentence. Current state-of-the-art methods regard CSC as a sequence tagging task and fine-tune BERT-based models on sentence pairs. However, we note a critical flaw in the process of tagging one character to another, that the correction is excessively conditioned on the error. This is opposite from human mindset, where individuals rephrase the complete sentence based on its semantics, rather than solely on the error patterns memorized before. Such a counter-intuitive learning process results in the bottleneck of generalizability and transferability of machine spelling correction. To address this, we propose Rephrasing Language Model (ReLM), where the model is trained to rephrase the entire sentence by infilling additional slots, instead of character-to-character tagging. This novel training paradigm achieves the new state-of-the-art results across fine-tuned and zero-shot CSC benchmarks, outperforming previous counterparts by a large margin. Our method also learns transferable language representation when CSC is jointly trained with other tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Multi-grained Evidence Inference for Multi-choice Reading Comprehension

arXiv

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arXiv 2023年

作者： Zhao, Yilin Zhao, Hai Duan, Sufeng Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China

Multi-choice Machine Reading Comprehension (MRC) is a major and challenging task for machines to answer questions according to provided options. Answers in multi-choice MRC cannot be directly extracted in the given passages, and essentially require machines capable of reasoning from accurate extracted evidence. However, the critical evidence may be as simple as just one word or phrase, while it is hidden in the given redundant, noisy passage with multiple linguistic hierarchies from phrase, fragment, sentence until the entire passage. We thus propose a novel general-purpose model enhancement which integrates multi-grained evidence comprehensively, named Multi-grained evidence inferencer (Mugen), to make up for the inability. Mugen extracts three different granularities of evidence: coarse-, middle- and fine-grained evidence, and integrates evidence with the original passages, achieving significant and consistent performance improvement on four multi-choice MRC benchmarks. © 2023, CC BY.

关键词： Benchmarking

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Raise Your Eyebrows Higher: Facilitating Emotional Communication in Social Virtual Reality Through Region-Specific Facial Expression Exaggeration 25

Raise Your Eyebrows Higher: Facilitating Emotional Communica...

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

作者： Wang, Xueyang Zhao, Sheng Wang, Yihe Han, Howard Ziyu Liu, Xinge Yi, Xin Tong, Xin Li, Hewu Institute for Network Sciences and Cyberspace Tsinghua University Beijing China Zhongguancun Laboratory Beijing China Weiyang College Tsinghua University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China Human-Computer Interaction Institute Carnegie Mellon University pittsburgh PA United States Beijing National Research Center for Information Science and Technology Beijing China Thrust of Computational Media and Arts Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

ISBN: (纸本)9798400713941

While exaggerated facial expressions in cartoon avatars can enhance emotional communication in social virtual reality (VR), they risk triggering the uncanny valley effect. Our research reveals that this effect varies significantly across different emotions. In Study 1 (N=30), participants evaluated scaled facial expressions during simulated VR conversations. We found that expression exaggeration had opposing effects: it decreased facial realism for joy, surprise, and disgust due to overly dramatic mouth movements, while enhancing realism for fear, sadness, and anger - emotions that rely on upper facial expressions typically constrained by HMD pressure. Based on these findings, we developed a region-specific facial expression exaggeration strategy that enhances under-expressed upper facial features while maintaining natural lower facial movements. Study 2 (N=20) validated this approach, demonstrating enhanced emotional intensity and contagion for negative emotions while mitigating the uncanny valley effect. Our research provides practical guidelines for optimizing avatar-mediated emotional communication in social VR environments. © 2025 Copyright held by the owner/author(s).

关键词： Cartoon Avatars Facial Expression Exaggeration Social Virtual Reality Uncanny Valley Effect User Empathy

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