Tootfinder

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Chatbot apologies: Beyond bullshit
P. D. Magnus, Alessandra Buccella, Jason D'Cruz

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- "I Always Felt that SomethingWasWrong.": Understanding Compliance Risks and Mitigation Strategies...
Siying Hu, Piaohong Wang, Ka I Chan, Yaxing Yao, Zhicong Lu

Why Robots Are Bad at Detecting Their Mistakes: Limitations of Miscommunication Detection in Human-Robot Dialogue
Ruben Janssens, Jens De Bock, Sofie Labat, Eva Verhelst, Veronique Hoste, Tony Belpaeme
https://arxiv.org/abs/2506.20268

Why Robots Are Bad at Detecting Their Mistakes: Limitations of Miscommunication Detection in Human-Robot Dialogue
Detecting miscommunication in human-robot interaction is a critical function for maintaining user engagement and trust. While humans effortlessly detect communication errors in conversations through both verbal and non-verbal cues, robots face significant challenges in interpreting non-verbal feedback, despite advances in computer vision for recognizing affective expressions. This research evaluates the effectiveness of machine learning models in detecting miscommunications in robot dialogue. U…

[2025-07-28 Mon (UTC), 23 new articles found for cs.HC Human-Computer Interaction]
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Environmental (in)considerations in the Design of Smartphone Settings
Thomas Thibault, L\'ea Mosesso, Camille Adam, Aur\'elien Tabard, Ana\"elle Beignon, Nolwenn Maudet
https://arxiv.org/abs/2507.19094

Environmental (in)considerations in the Design of Smartphone Settings
Designing for sufficiency is one of many approaches that could foster more moderate and sustainable digital practices. Based on the Sustainable Information and Communication Technologies (ICT) and Human-Computer Interaction (HCI) literature, we identify five environmental settings categories. However, our analysis of three mobile OS and nine representative applications shows an overall lack of environmental concerns in settings design, leading us to identify six pervasive anti-patterns. Environ…

SImpHAR: Advancing impedance-based human activity recognition using 3D simulation and text-to-motion models
Lala Shakti Swarup Ray, Mengxi Liu, Deepika Gurung, Bo Zhou, Sungho Suh, Paul Lukowicz
https://arxiv.org/abs/2507.06405

SImpHAR: Advancing impedance-based human activity recognition using 3D simulation and text-to-motion models
Human Activity Recognition (HAR) with wearable sensors is essential for applications in healthcare, fitness, and human-computer interaction. Bio-impedance sensing offers unique advantages for fine-grained motion capture but remains underutilized due to the scarcity of labeled data. We introduce SImpHAR, a novel framework addressing this limitation through two core contributions. First, we propose a simulation pipeline that generates realistic bio-impedance signals from 3D human meshes using sho…

Perspectives on How Sociology Can Advance Theorizing about Human-Chatbot Interaction and Developing Chatbots for Social Good
Celeste Campos-Castillo, Xuan Kang, Linnea I. Laestadius
https://arxiv.org/abs/2507.05030

Perspectives on How Sociology Can Advance Theorizing about Human-Chatbot Interaction and Developing Chatbots for Social Good
Recently, research into chatbots (also known as conversational agents, AI agents, voice assistants), which are computer applications using artificial intelligence to mimic human-like conversation, has grown sharply. Despite this growth, sociology lags other disciplines (including computer science, medicine, psychology, and communication) in publishing about chatbots. We suggest sociology can advance understanding of human-chatbot interaction and offer four sociological theories to enhance extan…

Capsule Network-Based Semantic Intent Modeling for Human-Computer Interaction
Shixiao Wang, Yifan Zhuang, Runsheng Zhang, Zhijun Song
https://arxiv.org/abs/2507.00540

Capsule Network-Based Semantic Intent Modeling for Human-Computer Interaction
This paper proposes a user semantic intent modeling algorithm based on Capsule Networks to address the problem of insufficient accuracy in intent recognition for human-computer interaction. The method represents semantic features in input text through a vectorized capsule structure. It uses a dynamic routing mechanism to transfer information across multiple capsule layers. This helps capture hierarchical relationships and part-whole structures between semantic entities more effectively. The mod…

[2025-06-27 Fri (UTC), 11 new articles found for cs.HC Human-Computer Interaction]
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Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Interrogating AI: Characterizing Emergent Playful Interactions with ChatGPT
Mohammad Ronagh Nikghalb, Jinghui Cheng

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Data Quality in Crowdsourcing and Spamming Behavior Detection
Yang Ba, Michelle V. Mancenido, Erin K. Chiou, Rong Pan

You Only Render Once: Enhancing Energy and Computation Efficiency of Mobile Virtual Reality
Xingyu Chen, Xinmin Fang, Shuting Zhang, Xinyu Zhang, Liang He, Zhengxiong Li
https://arxiv.org/abs/2506.15183

You Only Render Once: Enhancing Energy and Computation Efficiency of Mobile Virtual Reality
Mobile Virtual Reality (VR) is essential to achieving convenient and immersive human-computer interaction and realizing emerging applications such as Metaverse. However, existing VR technologies require two separate renderings of binocular images, causing a significant bottleneck for mobile devices with limited computing capability and power supply. This paper proposes an approach to rendering optimization for mobile VR called EffVR. By utilizing the per-pixel attribute, EffVR can generate bino…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- A Scoping Review of Functional Near-Infrared Spectroscopy (fNIRS) Applications in Game-Based Lear...
Sharmin, Lucero-Palacios, Kiafar, Abrar, Al-Ratrout, Raikwar, Barmaki

Animal Interaction with Autonomous Mobility Systems: Designing for Multi-Species Coexistence
Tram Thi Minh Tran, Xinyan Yu, Marius Hoggenmueller, Callum Paker, Paul Schmitt, Julie Stephany Berrio Perez, Stewart Worrall, Martin Tomitsch
https://arxiv.org/abs/2507.16258

Animal Interaction with Autonomous Mobility Systems: Designing for Multi-Species Coexistence
Autonomous mobility systems increasingly operate in environments shared with animals, from urban pets to wildlife. However, their design has largely focused on human interaction, with limited understanding of how non-human species perceive, respond to, or are affected by these systems. Motivated by research in Animal-Computer Interaction (ACI) and more-than-human design, this study investigates animal interactions with autonomous mobility through a multi-method approach combining a scoping revi…

This https://arxiv.org/abs/2505.19669 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Zero-Shot Streaming Text to Speech Synthesis with Transducer and Auto-Regressive Modeling
Zero-shot streaming text-to-speech is an important research topic in human-computer interaction. Existing methods primarily use a lookahead mechanism, relying on future text to achieve natural streaming speech synthesis, which introduces high processing latency. To address this issue, we propose SMLLE, a streaming framework for generating high-quality speech frame-by-frame. SMLLE employs a Transducer to convert text into semantic tokens in real time while simultaneously obtaining duration align…

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model
Ailin Huang, Bingxin Li, Bruce Wang, Boyong Wu, Chao Yan, Chengli Feng, Heng Wang, Hongyu Zhou, Hongyuan Wang, Jingbei Li, Jianjian Sun, Joanna Wang, Mingrui Chen, Peng Liu, Ruihang Miao, Shilei Jiang, Tian Fei, Wang You, Xi Chen, Xuerui Yang, Yechang Huang, Yuxiang Zhang, Zheng Ge, Zheng Gong, Zhewei Huang, Zixin Zhang, Bin Wang, Bo Li, Buyun Ma, Changxin Miao, Changyi Wan, Chen Xu, Dapeng Shi, Dingyuan Hu, Enle…

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model
Large Audio-Language Models (LALMs) have significantly advanced intelligent human-computer interaction, yet their reliance on text-based outputs limits their ability to generate natural speech responses directly, hindering seamless audio interactions. To address this, we introduce Step-Audio-AQAA, a fully end-to-end LALM designed for Audio Query-Audio Answer (AQAA) tasks. The model integrates a dual-codebook audio tokenizer for linguistic and semantic feature extraction, a 130-billion-parameter…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series
Ziquan Deng, Xiwei Xuan, Kwan-Liu Ma, Zhaodan Kong

The Role of Partisan Culture in Mental Health Language Online
Sachin R. Pendse, Ben Rochford, Neha Kumar, Munmun De Choudhury
https://arxiv.org/abs/2506.20377

The Role of Partisan Culture in Mental Health Language Online
The impact of culture on how people express distress in online support communities is increasingly a topic of interest within Computer Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI). In the United States, distinct cultures have emerged from each of the two dominant political parties, forming a primary lens by which people navigate online and offline worlds. We examine whether partisan culture may play a role in how U.S. Republican and Democrat users of online mental heal…

MMOC: Self-Supervised EEG Emotion Recognition Framework with Multi-Model Online Collaboration
Hanqi Wang, Yang Liu, Peng Ye, Liang Song
https://arxiv.org/abs/2507.03977

MMOC: Self-Supervised EEG Emotion Recognition Framework with Multi-Model Online Collaboration
Electroencephalography (EEG) emotion recognition plays a crucial role in human-computer interaction, particularly in healthcare and neuroscience. While supervised learning has been widely used, its reliance on manual annotations introduces high costs and potential bias. Self-supervised learning (SSL) offers a promising alternative by generating labels through pretext tasks. However, high inter-subject variability in EEG signals leads to significant data drift, limiting self-supervised models' g…

SVD: Spatial Video Dataset
M. H. Izadimehr, Milad Ghanbari, Guodong Chen, Wei Zhou, Xiaoshuai Hao, Mallesham Dasari, Christian Timmerer, Hadi Amirpour
https://arxiv.org/abs/2506.06037

SVD: Spatial Video Dataset
Stereoscopic video has long been the subject of research due to its capacity to deliver immersive three-dimensional content across a wide range of applications, from virtual and augmented reality to advanced human-computer interaction. The dual-view format inherently provides binocular disparity cues that enhance depth perception and realism, making it indispensable for fields such as telepresence, 3D mapping, and robotic vision. Until recently, however, end-to-end pipelines for capturing, enco…

Foundation of Affective Computing and Interaction
Changzeng Fu
https://arxiv.org/abs/2506.15497 https://arxiv.org/pdf/2506.15497

Foundation of Affective Computing and Interaction
This book provides a comprehensive exploration of affective computing and human-computer interaction technologies. It begins with the historical development and basic concepts of human-computer interaction, delving into the technical frameworks and practical applications of emotional computing, visual interaction, voice interaction, brain-computer interfaces, physiological electrical signal analysis, and social robotics. The book covers a wide range of topics, including the psychological and ne…

This https://arxiv.org/abs/2505.20007 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking Model
Emotion plays a fundamental role in human interaction, and therefore systems capable of identifying emotions in speech are crucial in the context of human-computer interaction. Speech emotion recognition (SER) is a challenging problem, particularly in natural speech and when the available data is imbalanced across emotions. This paper presents our proposed system in the context of the 2025 Speech Emotion Recognition in Naturalistic Conditions Challenge. Our proposed architecture leverages cross…

[2025-06-26 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]
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Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- The Paradox of Spreadsheet Self-Efficacy: Social Incentives for Informal Knowledge Sharing in End...
Qing (Nancy), Xia, Advait Sarkar, Duncan P. Brumby, Anna Cox

Pureformer-VC: Non-parallel Voice Conversion with Pure Stylized Transformer Blocks and Triplet Discriminative Training
Wenhan Yao, Fen Xiao, Xiarun Chen, Jia Liu, YongQiang He, Weiping Wen
https://arxiv.org/abs/2506.08348

Pureformer-VC: Non-parallel Voice Conversion with Pure Stylized Transformer Blocks and Triplet Discriminative Training
As a foundational technology for intelligent human-computer interaction, voice conversion (VC) seeks to transform speech from any source timbre into any target timbre. Traditional voice conversion methods based on Generative Adversarial Networks (GANs) encounter significant challenges in precisely encoding diverse speech elements and effectively synthesising these elements into natural-sounding converted speech. To overcome these limitations, we introduce Pureformer-VC, an encoder-decoder frame…

AutoGraph: A Knowledge-Graph Framework for Modeling Interface Interaction and Automating Procedure Execution in Digital Nuclear Control Rooms
Xingyu Xiao, Jiejuan Tong, Jun Sun, Zhe Sui, Jingang Liang, Hongru Zhao, Jun Zhao, Haitao Wang
https://arxiv.org/abs/2506.18727

AutoGraph: A Knowledge-Graph Framework for Modeling Interface Interaction and Automating Procedure Execution in Digital Nuclear Control Rooms
Digitalization in nuclear power plant (NPP) control rooms is reshaping how operators interact with procedures and interface elements. However, existing computer-based procedures (CBPs) often lack semantic integration with human-system interfaces (HSIs), limiting their capacity to support intelligent automation and increasing the risk of human error, particularly under dynamic or complex operating conditions. In this study, we present AutoGraph, a knowledge-graph-based framework designed to form…

Can GPT-4o Evaluate Usability Like Human Experts? A Comparative Study on Issue Identification in Heuristic Evaluation
Guilherme Guerino, Luiz Rodrigues, Bruna Capeleti, Rafael Ferreira Mello, Andr\'e Freire, Luciana Zaina
https://arxiv.org/abs/2506.16345

Can GPT-4o Evaluate Usability Like Human Experts? A Comparative Study on Issue Identification in Heuristic Evaluation
Heuristic evaluation is a widely used method in Human-Computer Interaction (HCI) to inspect interfaces and identify issues based on heuristics. Recently, Large Language Models (LLMs), such as GPT-4o, have been applied in HCI to assist in persona creation, the ideation process, and the analysis of semi-structured interviews. However, considering the need to understand heuristics and the high degree of abstraction required to evaluate them, LLMs may have difficulty conducting heuristic evaluation…

This https://arxiv.org/abs/2505.15799 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

The Agentic Economy
Generative AI has transformed human-computer interaction by enabling natural language interfaces and the emergence of autonomous agents capable of acting on users' behalf. While early applications have improved individual productivity, these gains have largely been confined to predefined tasks within existing workflows. We argue that the more profound economic impact lies in reducing communication frictions between consumers and businesses. This shift could reorganize markets, redistribute powe…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Using Generative Artificial Intelligence Creatively in the Classroom and Research: Examples and L...
Maria J. Molina, Amy McGovern, Jhayron S. Perez-Carrasquilla, Xiaowen Li, Robin L. Tanamachi
…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[2/2]:
- Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Custome...
Varun Mannam, Zhenyu Shi

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/2]:
- Case Law Grounding: Using Precedents to Align Decision-Making for Humans and AI
Quan Ze Chen, Amy X. Zhang

SPBA: Utilizing Speech Large Language Model for Backdoor Attacks on Speech Classification Models
Wenhan Yao, Fen Xiao, Xiarun Chen, Jia Liu, YongQiang He, Weiping Wen
https://arxiv.org/abs/2506.08346

SPBA: Utilizing Speech Large Language Model for Backdoor Attacks on Speech Classification Models
Deep speech classification tasks, including keyword spotting and speaker verification, are vital in speech-based human-computer interaction. Recently, the security of these technologies has been revealed to be susceptible to backdoor attacks. Specifically, attackers use noisy disruption triggers and speech element triggers to produce poisoned speech samples that train models to become vulnerable. However, these methods typically create only a limited number of backdoors due to the inherent cons…

[2025-06-25 Wed (UTC), 13 new articles found for cs.HC Human-Computer Interaction]
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[2025-07-25 Fri (UTC), 27 new articles found for cs.HC Human-Computer Interaction]
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This https://arxiv.org/abs/2505.23018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMM_…

EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations
In recent years, emotion recognition plays a critical role in applications such as human-computer interaction, mental health monitoring, and sentiment analysis. While datasets for emotion analysis in languages such as English have proliferated, there remains a pressing need for high-quality, comprehensive datasets tailored to the unique linguistic, cultural, and multimodal characteristics of Chinese. In this work, we propose \textbf{EmotionTalk}, an interactive Chinese multimodal emotion datase…

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning
Zhao Ren, Rathi Adarshi Rammohan, Kevin Scheck, Sheng Li, Tanja Schultz
https://arxiv.org/abs/2507.07806

End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning
Emotion and intent recognition from speech is essential and has been widely investigated in human-computer interaction. The rapid development of social media platforms, chatbots, and other technologies has led to a large volume of speech data streaming from users. Nevertheless, annotating such data manually is expensive, making it challenging to train machine learning models for recognition purposes. To this end, we propose applying semi-supervised learning to incorporate a large scale of unlab…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Benchmarking Mobile Device Control Agents across Diverse Configurations
Juyong Lee, Taywon Min, Minyong An, Dongyoon Hahm, Haeone Lee, Changyeon Kim, Kimin Lee

[2025-06-24 Tue (UTC), 22 new articles found for cs.HC Human-Computer Interaction]
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[2025-07-24 Thu (UTC), 16 new articles found for cs.HC Human-Computer Interaction]
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A Novel Hybrid Deep Learning Technique for Speech Emotion Detection using Feature Engineering
Shahana Yasmin Chowdhury, Bithi Banik, Md Tamjidul Hoque, Shreya Banerjee
https://arxiv.org/abs/2507.07046

A Novel Hybrid Deep Learning Technique for Speech Emotion Detection using Feature Engineering
Nowadays, speech emotion recognition (SER) plays a vital role in the field of human-computer interaction (HCI) and the evolution of artificial intelligence (AI). Our proposed DCRF-BiLSTM model is used to recognize seven emotions: neutral, happy, sad, angry, fear, disgust, and surprise, which are trained on five datasets: RAVDESS (R), TESS (T), SAVEE (S), EmoDB (E), and Crema-D (C). The model achieves high accuracy on individual datasets, including 97.83% on RAVDESS, 97.02% on SAVEE, 95.10% for …

Initiating and Replicating the Observations of Interactional Properties by User Studies Optimizing Applicative Prototypes
Guillaume Rivi\`ere
https://arxiv.org/abs/2507.13923

Initiating and Replicating the Observations of Interactional Properties by User Studies Optimizing Applicative Prototypes
The science of Human-Computer Interaction (HCI) is populated by isolated empirical findings, often tied to specific technologies, designs, and tasks. This paper proposes a formalization of user interaction observations (instead of user interfaces) and an associated revealing method (interaction loop diffraction). The resulting interactional properties that are studied in a calibrated manner, are well suited to replication across various conditions (prototypes, technologies, tasks, and user prof…

EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations
Haoqin Sun, Xuechen Wang, Jinghua Zhao, Shiwan Zhao, Jiaming Zhou, Hui Wang, Jiabei He, Aobo Kong, Xi Yang, Yequan Wang, Yonghua Lin, Yong Qin
https://arxiv.org/abs/2505.23018

EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations
In recent years, emotion recognition plays a critical role in applications such as human-computer interaction, mental health monitoring, and sentiment analysis. While datasets for emotion analysis in languages such as English have proliferated, there remains a pressing need for high-quality, comprehensive datasets tailored to the unique linguistic, cultural, and multimodal characteristics of Chinese. In this work, we propose \textbf{EmotionTalk}, an interactive Chinese multimodal emotion datase…

Layered Interactions: Exploring Non-Intrusive Digital Craftsmanship Design Through Lacquer Art Interfaces
Yan Dong, Hanjie Yu, Yanran Chen, Zipeng Zhang, Qiong Wu
https://arxiv.org/abs/2507.17430

Layered Interactions: Exploring Non-Intrusive Digital Craftsmanship Design Through Lacquer Art Interfaces
Integrating technology with the distinctive characteristics of craftsmanship has become a key issue in the field of digital craftsmanship. This paper introduces Layered Interactions, a design approach that seamlessly merges Human-Computer Interaction (HCI) technologies with traditional lacquerware craftsmanship. By leveraging the multi-layer structure and material properties of lacquerware, we embed interactive circuits and integrate programmable hardware within the layers, creating tangible in…

[2025-07-23 Wed (UTC), 15 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-23 Mon (UTC), 23 new articles found for cs.HC Human-Computer Interaction]
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CLEP-DG: Contrastive Learning for Speech Emotion Domain Generalization via Soft Prompt Tuning
Jiacheng Shi, Yanfu Zhang, Ye Gao
https://arxiv.org/abs/2507.04048

CLEP-DG: Contrastive Learning for Speech Emotion Domain Generalization via Soft Prompt Tuning
Speech Emotion Recognition (SER) is fundamental to affective computing and human-computer interaction, yet existing models struggle to generalize across diverse acoustic conditions. While Contrastive Language-Audio Pretraining (CLAP) provides strong multimodal alignment, it lacks dedicated mechanisms for capturing emotional cues, making it suboptimal for SER. To address this, we propose CLEP-DG, a framework that enhances CLAP's robustness in emotion recognition. First, we fine-tune CLAP to obta…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges
Bozkir, S\Ozdel, Wang, David-John, Gao, Butler, Jain, Kasneci

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
Gaze-informed Signatures of Trust and Collaboration in Human-Autonomy Teams

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Implementation Considerations for Automated AI Grading of Student Work
Zewei (Victor), Tian, Alex Liu, Lief Esbenshade, Shawon Sarkar, Zachary Zhang, Kevin He, Min Sun

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- A Design Space for Multiscale Visualization
Mara Solen, Matt Oddo, Tamara Munzner

This https://arxiv.org/abs/2406.15119 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation
Speech emotion recognition (SER) plays a crucial role in human-computer interaction. The emergence of edge devices in the Internet of Things (IoT) presents challenges in constructing intricate deep learning models due to constraints in memory and computational resources. Moreover, emotional speech data often contains private information, raising concerns about privacy leakage during the deployment of SER models. To address these challenges, we propose a data distillation framework to facilitate…

[2025-07-21 Mon (UTC), 12 new articles found for cs.HC Human-Computer Interaction]
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Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Qualitative Study for LLM-assisted Design Study Process: Strategies, Challenges, and Roles
Shaolun Ruan, Rui Sheng, Xiaolin Wen, Jiachen Wang, Tianyi Zhang, Yong Wang, Tim Dwyer, Jiannan Li

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
Aptly: Making Mobile Apps from Natural Language
https://

[2025-06-20 Fri (UTC), no new articles found for cs.HC Human-Computer Interaction]
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Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Cluster Haptic Texture Database: Haptic Texture Database with Varied Velocity-Direction Sliding C...
Michikuni Eguchi, Tomohiro Hayase, Yuichi Hiroi, Takefumi Hiraki

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
Predicting Trust Dynamics Type Using Seven Personal Characteristics
http…

Intelligent Virtual Sonographer (IVS): Enhancing Physician-Robot-Patient Communication
Tianyu Song, Feng Li, Yuan Bi, Angelos Karlas, Amir Yousefi, Daniela Branzan, Zhongliang Jiang, Ulrich Eck, Nassir Navab
https://arxiv.org/abs/2507.13052

Intelligent Virtual Sonographer (IVS): Enhancing Physician-Robot-Patient Communication
The advancement and maturity of large language models (LLMs) and robotics have unlocked vast potential for human-computer interaction, particularly in the field of robotic ultrasound. While existing research primarily focuses on either patient-robot or physician-robot interaction, the role of an intelligent virtual sonographer (IVS) bridging physician-robot-patient communication remains underexplored. This work introduces a conversational virtual agent in Extended Reality (XR) that facilitates …

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Human-AI Collaboration for Wearable Technology Component Standardization
Andrew M. Lydner

Screen Reader Users in the Vibe Coding Era: Adaptation, Empowerment, and New Accessibility Landscape
Nan Chen, Luna K. Qiu, Arran Zeyu Wang, Zilong Wang, Yuqing Yang
https://arxiv.org/abs/2506.13270

Screen Reader Users in the Vibe Coding Era: Adaptation, Empowerment, and New Accessibility Landscape
The rise of generative AI agents has reshaped human-computer interaction and computer-supported cooperative work by shifting users' roles from direct task execution to supervising machine-driven actions, especially in programming (e.g., "vibe coding"). However, there is limited understanding of how screen reader users engage with these systems in practice. To address this gap, we conducted a longitudinal study with 16 screen reader users, exploring their experiences with AI code assistants in d…

[2025-06-19 Thu (UTC), 20 new articles found for cs.HC Human-Computer Interaction]
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Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI Literature
Shuning Zhang, Hui Wang, Xin Yi
https://arxiv.org/abs/2507.06000

Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI Literature
As Artificial Intelligence (AI) increasingly becomes an active collaborator in co-creation, understanding the distribution and dynamic of agency is paramount. The Human-Computer Interaction (HCI) perspective is crucial for this analysis, as it uniquely reveals the interaction dynamics and specific control mechanisms that dictate how agency manifests in practice. Despite this importance, a systematic synthesis mapping agency configurations and control mechanisms within the HCI/CSCW literature is…

[2025-07-18 Fri (UTC), 13 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-18 Wed (UTC), 18 new articles found for cs.HC Human-Computer Interaction]
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[2025-07-17 Thu (UTC), 18 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-17 Tue (UTC), 22 new articles found for cs.HC Human-Computer Interaction]
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Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- DMER-Ranker: Learning to Rank Emotion Descriptions in the Absence of Ground Truth
Lian, Sun, Chen, Cheng, Zhang, Jia, Ma, Ma, Peng, Tao

[2025-07-16 Wed (UTC), 10 new articles found for cs.HC Human-Computer Interaction]
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Exploring a Gamified Personality Assessment Method through Interaction with Multi-Personality LLM Agents
Baiqiao Zhang, Xiangxian Li, Chao Zhou, Xinyu Gai, Zhifeng Liao, Juan Liu, Xue Yang, Niqi Liu, Xiaojuan Ma, Yong-jin Liu, Yulong Bian
https://arxiv.org/abs/2507.04005

Exploring a Gamified Personality Assessment Method through Interaction with Multi-Personality LLM Agents
The execution of effective and imperceptible personality assessments is receiving increasing attention in psychology and human-computer interaction fields. This study explores an interactive approach for personality assessment, focusing on the multiplicity of personality representation. We propose a framework of gamified personality assessment through multi-personality representations (Multi-PR GPA). The framework leverages Large Language Models to empower virtual agents with diverse personalit…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideation
Yiren Liu, Pranav Sharma, Mehul Jitendra Oswal, Haijun Xia, Yun Huang

Towards Creating Infrastructures for Values and Ethics Work in the Production of Software Technologies
Richmond Y. Wong
https://arxiv.org/abs/2507.11490 ht…

Towards Creating Infrastructures for Values and Ethics Work in the Production of Software Technologies
Recognizing how technical systems can embody social values or cause harms, human-computer interaction (HCI) research often approaches addressing values and ethics in design by creating tools to help tech workers integrate social values into the design of products. While useful, these approaches usually do not consider the politics embedded in the broader processes, organizations, social systems, and governance structures that affect the types of actions that tech workers can take to address val…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- EvAlignUX: Advancing UX Evaluation through LLM-Supported Metrics Exploration
Qingxiao Zheng, Minrui Chen, Pranav Sharma, Yiliu Tang, Mehul Oswal, Yiren Liu, Yun Huang

[2025-07-14 Mon (UTC), 11 new articles found for cs.HC Human-Computer Interaction]
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- Making Physical Objects with Generative AI and Robotic Assembly: Considering Fabrication Constrai...
Alexander Htet Kyaw, Se Hwan Jeon, Miana Smith, Neil Gershenfeld

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/2]:
- Exploring Emotional and Social Dynamics in Mobile Usage During Home Confinement
Gao, Nolan, Ji, Rumi, Heinisch, Anderson, David, Salim

[2025-06-13 Fri (UTC), 14 new articles found for cs.HC Human-Computer Interaction]
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Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
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- Look and Talk: Seamless AI Assistant Interaction with Gaze-Triggered Activation
Zhang Qing, Rekimoto Jun

Esports and expertise: what competitive gaming can teach us about mastery
Ben Boudaoud, Josef Spjut, Joohwan Kim, Arjun Madhusudan, Benjamin Watson
https://arxiv.org/abs/2507.05446

Esports and expertise: what competitive gaming can teach us about mastery
Historically, much research and development in human computer interaction has focused on atomic and generalizable tasks, where task completion time indicates productivity. However, the emergence of competitive games and esports reminds us of an alternative perspective on human performance in HCI: mastery of higher-level, holistic practices. Just as a world-renowned artist is rarely evaluated for their individual brush strokes, so skilled competitive gamers rarely succeed solely by completing in…

Infrastructuring Contestability: A Framework for Community-Defined AI Value Pluralism
Andreas Mayer
https://arxiv.org/abs/2507.05187 https://

Infrastructuring Contestability: A Framework for Community-Defined AI Value Pluralism
The proliferation of AI-driven systems presents a fundamental challenge to Human-Computer Interaction (HCI) and Computer-Supported Cooperative Work (CSCW), often diminishing user agency and failing to account for value pluralism. Current approaches to value alignment, which rely on centralized, top-down definitions, lack the mechanisms for meaningful contestability. This leaves users and communities unable to challenge or shape the values embedded in the systems that govern their digital lives,…

[2025-06-12 Thu (UTC), 12 new articles found for cs.HC Human-Computer Interaction]
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Spatial tangible user interfaces for cognitive assessment and training
Ehud Sharlin, Yuichi Itoh, Benjamin Watson, Yoshifumi Kitamura, Steve Sutphen, Lili Liu, Fumio Kishino
https://arxiv.org/abs/2507.01944

Spatial tangible user interfaces for cognitive assessment and training
This paper discusses Tangible User Interfaces (TUIs) and their potential impact on cognitive assessment and cognitive training. We believe that TUIs, and particularly a subset that we dub spatial TUIs, can extend human computer interaction beyond some of its current limitations. Spatial TUIs exploit human innate spatial and tactile ability in an intuitive and direct manner, affording interaction paradigms that are practically impossible using current interface technology. As proof-of-concept we…

[2025-07-11 Fri (UTC), 6 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-11 Wed (UTC), 13 new articles found for cs.HC Human-Computer Interaction]
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- Cluster Haptic Texture Database: Haptic Texture Database with Varied Velocity-Direction Sliding C...
Michikuni Eguchi, Tomohiro Hayase, Yuichi Hiroi, Takefumi Hiraki

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- Decoding Neural Signals: Invasive BMI Review
Firuzi, Bokani, Hassan, Ahmadyani, Abdi, Naderi, Ebrahimi

[2025-07-10 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]
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Exploring the Convergence of HCI and Evolving Technologies in Information Systems
Rajan Das Gupta, Ashikur Rahman, Md Imrul Hasan Showmick, Md. Yeasin Rahat, Md. Jakir Hossen
https://arxiv.org/abs/2506.08549

Exploring the Convergence of HCI and Evolving Technologies in Information Systems
Modern technology driven information systems are part of our daily lives. However, this deep integration poses new challenges to the human computer interaction (HCI) professionals. With the rapid growth of mobile and cloud computing and the Internet of Things (IoT), the demand for HCI specialists to design user-friendly and adaptable interfaces has never been more pressing. Especially for diverse user groups such as children, the elderly and people with disabilities who need interfaces tailored…

[2025-07-09 Wed (UTC), 14 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-09 Mon (UTC), 16 new articles found for cs.HC Human-Computer Interaction]
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- Heuristics for AI-driven Graphical Asset Generation Tools in Game Design and Development Pipeline...
Kaisei Fukaya, Damon Daylamani-Zad, Harry Agius

[2025-06-06 Fri (UTC), 10 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-05 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]
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[2025-07-04 Fri (UTC), 19 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-04 Wed (UTC), 12 new articles found for cs.HC Human-Computer Interaction]
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This https://arxiv.org/abs/2504.13865 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

A Survey on (M)LLM-Based GUI Agents
Graphical User Interface (GUI) Agents have emerged as a transformative paradigm in human-computer interaction, evolving from rule-based automation scripts to sophisticated AI-driven systems capable of understanding and executing complex interface operations. This survey provides a comprehensive examination of the rapidly advancing field of LLM-based GUI Agents, systematically analyzing their architectural foundations, technical components, and evaluation methodologies. We identify and analyze f…

[2025-07-03 Thu (UTC), 14 new articles found for cs.HC Human-Computer Interaction]
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[2025-07-02 Wed (UTC), 17 new articles found for cs.HC Human-Computer Interaction]
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[2025-07-01 Tue (UTC), 30 new articles found for cs.HC Human-Computer Interaction]
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[2025-06-30 Mon (UTC), 11 new articles found for cs.HC Human-Computer Interaction]
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Access InContext: Futuring Accessible Prototyping Tools and Methods
Patricia Piedade, Peter A Hayton, Cynthia Bennett, Anna R L Carter, Clara Crivellaro, Alan Dix, Jess McGowan, Katta Spiel, Miriam Sturdee, Garreth W. Tigwell, Hugo Nicolau
https://arxiv.org/abs/2506.24057

Access InContext: Futuring Accessible Prototyping Tools and Methods
The popularity of accessibility research has grown recently, improving digital inclusion for people with disabilities. However, researchers, including those who have disabilities, have attempted to include people with disabilities in all aspects of design, and they have identified a myriad of practical accessibility barriers posed by tools and methods leveraged by human-computer interaction (HCI) researchers during prototyping. To build a more inclusive technological landscape, we must question…