arXiv subjects

Lik-Hang Lee

Publications and source records attributed to Lik-Hang Lee.

At least 37 records · Page 2Linked to original sources

arXiv2025

Metabook: A Mobile-to-Headset Pipeline for 3D Story Book Creation in Augmented Reality

The AR 3D book has shown significant potential in enhancing students' learning outcomes. However, the creation process of 3D books requires a significant investment of time, effort, and specialized skills. Thus, in this paper, we first conduct a three-day workshop investigating how AI can support the automated creation of 3D books. Informed by the design insights derived from the workshop, we developed Metabook, a system that enables even novice users to create 3D books from text automatically. To our knowledge, Metabook is the first system to offer end-to-end 3D book generation. A follow-up study with adult users indicates that Metabook enables inexperienced users to create 3D books, achieving reduced efforts and shortened preparation time. We subsequently recruited 22 children to examine the effects of AR 3D books on children's learning compared with paper-based books. The findings indicate that 3D books significantly enhance children's interest, improve memory retention, and reduce cognitive load, though no significant improvement was observed in comprehension. We conclude by discussing strategies for more effectively leveraging 3D books to support children's learning and offer practical recommendations for educators.

cs.HC↗

arXiv2025

A Comprehensive Survey of Electrical Stimulation Haptic Feedback in Human-Computer Interaction

Haptic perception and feedback play a pivotal role in interactive experiences, forming an essential component of human-computer interaction (HCI). In recent years, the field of haptic interaction has witnessed significant advancements, particularly in the area of electrical haptic feedback, driving innovation across various domains. To gain a comprehensive understanding of the current state of research and the latest developments in electrical haptic interaction, this study systematically reviews the literature in this area. Our investigation covers key aspects including haptic devices, haptic perception mechanisms, the comparison and integration of electrical haptic feedback with other feedback modalities, and their diverse applications. Specifically, we conduct a systematic analysis of 110 research papers to explore the forefront of electrical haptic feedback, providing insights into its latest trends, challenges, and future directions.

cs.HC↗

arXiv2025

Towards Enhanced Learning through Presence: A Systematic Review of Presence in Virtual Reality Across Tasks and Disciplines

The rising interest in Virtual Reality (VR) technology has sparked a desire to create immersive learning platforms capable of handling various tasks across environments. Through immersive interfaces, users can engage deeply with virtual environments, enhancing both learning outcomes and task performance. In fields such as education, engineering, and collaboration, presence has emerged as a critical factor influencing user engagement, motivation, and skill mastery. This review provides a comprehensive examination of the role of presence across different tasks and disciplines, exploring how its design impacts learning outcomes. Using a systematic search strategy based on the PRISMA method, we screened 2,793 articles and included 78 studies that met our inclusion criteria. We conducted a detailed classification and analysis of different types of presence in VR environments, including spatial presence, social presence, co-presence, self-presence, and cognitive presence. This review emphasizes how these varied types of presence affect learning outcomes across tasks and fields, and examines how design elements and interaction techniques shape presence and subsequently impact learning outcomes. We also summarize trends and future directions, identifying research gaps and opportunities to improve learning outcomes by enhancing presence in VR environments, thus offering guidance and insight for future research on VR presence and learning effectiveness.

cs.HC↗

arXiv2025

TeamPortal: Exploring Virtual Reality Collaboration Through Shared and Manipulating Parallel Views

Virtual Reality (VR) offers a unique collaborative experience, with parallel views playing a pivotal role in Collaborative Virtual Environments by supporting the transfer and delivery of items. Sharing and manipulating partners' views provides users with a broader perspective that helps them identify the targets and partner actions. We proposed TeamPortal accordingly and conducted two user studies with 72 participants (36 pairs) to investigate the potential benefits of interactive, shared perspectives in VR collaboration. Our first study compared ShaView and TeamPortal against a baseline in a collaborative task that encompassed a series of searching and manipulation tasks. The results show that TeamPortal significantly reduced movement and increased collaborative efficiency and social presence in complex tasks. Following the results, the second study evaluated three variants: TeamPortal+, SnapTeamPortal+, and DropTeamPortal+. The results show that both SnapTeamPortal+ and DropTeamPortal+ improved task efficiency and willingness to further adopt these technologies, though SnapTeamPortal+ reduced co-presence. Based on the findings, we proposed three design implications to inform the development of future VR collaboration systems.

cs.HC↗

arXiv2024

LMLPA: Language Model Linguistic Personality Assessment

Large Language Models (LLMs) are increasingly used in everyday life and research. One of the most common use cases is conversational interactions, enabled by the language generation capabilities of LLMs. Just as between two humans, a conversation between an LLM-powered entity and a human depends on the personality of the conversants. However, measuring the personality of a given LLM is currently a challenge. This paper introduces the Language Model Linguistic Personality Assessment (LMLPA), a system designed to evaluate the linguistic personalities of LLMs. Our system helps to understand LLMs' language generation capabilities by quantitatively assessing the distinct personality traits reflected in their linguistic outputs. Unlike traditional human-centric psychometrics, the LMLPA adapts a personality assessment questionnaire, specifically the Big Five Inventory, to align with the operational capabilities of LLMs, and also incorporates the findings from previous language-based personality measurement literature. To mitigate sensitivity to the order of options, our questionnaire is designed to be open-ended, resulting in textual answers. Thus, the AI rater is needed to transform ambiguous personality information from text responses into clear numerical indicators of personality traits. Utilising Principal Component Analysis and reliability validations, our findings demonstrate that LLMs possess distinct personality traits that can be effectively quantified by the LMLPA. This research contributes to Human-Computer Interaction and Human-Centered AI, providing a robust framework for future studies to refine AI personality assessments and expand their applications in multiple areas, including education and manufacturing.

cs.CL↗

arXiv2024

Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era

Generative AI has made significant progress in recent years, with text-guided content generation being the most practical as it facilitates interaction between human instructions and AI-generated content (AIGC). Thanks to advancements in text-to-image and 3D modeling technologies, like neural radiance field (NeRF), text-to-3D has emerged as a nascent yet highly active research field. Our work conducts a comprehensive survey on this topic and follows up on subsequent research progress in the overall field, aiming to help readers interested in this direction quickly catch up with its rapid development. First, we introduce 3D data representations, including both Structured and non-Structured data. Building on this pre-requisite, we introduce various core technologies to achieve satisfactory text-to-3D results. Additionally, we present mainstream baselines and research directions in recent text-to-3D technology, including fidelity, efficiency, consistency, controllability, diversity, and applicability. Furthermore, we summarize the usage of text-to-3D technology in various applications, including avatar generation, texture generation, scene generation and 3D editing. Finally, we discuss the agenda for the future development of text-to-3D.

cs.CV↗

arXiv2024

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

The Segment Anything Model (SAM), developed by Meta AI Research, represents a significant breakthrough in computer vision, offering a robust framework for image and video segmentation. This survey provides a comprehensive exploration of the SAM family, including SAM and SAM 2, highlighting their advancements in granularity and contextual understanding. Our study demonstrates SAM's versatility across a wide range of applications while identifying areas where improvements are needed, particularly in scenarios requiring high granularity and in the absence of explicit prompts. By mapping the evolution and capabilities of SAM models, we offer insights into their strengths and limitations and suggest future research directions, including domain-specific adaptations and enhanced memory and propagation mechanisms. We believe that this survey comprehensively covers the breadth of SAM's applications and challenges, setting the stage for ongoing advancements in segmentation technology.

cs.CV↗

arXiv2024

Last Week with ChatGPT: A Weibo Study on Social Perspective Regarding ChatGPT for Education and Beyond

The application of AI-powered tools has piqued the interest of many fields, particularly in the academic community. This study uses ChatGPT, currently the most powerful and popular AI tool, as a representative example to analyze how the Chinese public perceives the potential of large language models (LLMs) for educational and general purposes. Although facing accessibility challenges, we found that the number of discussions on ChatGPT per month is 16 times that of Ernie Bot developed by Baidu, the most popular alternative product to ChatGPT in the mainland, making ChatGPT a more suitable subject for our analysis. The study also serves as the first effort to investigate the changes in public opinion as AI technologies become more advanced and intelligent. The analysis reveals that, upon first encounters with advanced AI that was not yet highly capable, some social media users believed that AI advancements would benefit education and society, while others feared that advanced AI, like ChatGPT, would make humans feel inferior and lead to problems such as cheating and a decline in moral principles. The majority of users remained neutral. Interestingly, with the rapid development and improvement of AI capabilities, public attitudes have tended to shift in a positive direction. We present a thorough analysis of the trending shift and a roadmap to ensure the ethical application of ChatGPT-like models in education and beyond.

cs.CY↗

arXiv2024

MetaDragonBoat: Exploring Paddling Techniques of Virtual Dragon Boating in a Metaverse Campus

The preservation of cultural heritage, as mandated by the United Nations Sustainable Development Goals (SDGs), is integral to sustainable urban development. This paper focuses on the Dragon Boat Festival, a prominent event in Chinese cultural heritage, and proposes leveraging Virtual Reality (VR), to enhance its preservation and accessibility. Traditionally, participation in the festival's dragon boat races was limited to elite athletes, excluding broader demographics. Our proposed solution, named MetaDragonBoat, enables virtual participation in dragon boat racing, offering immersive experiences that replicate physical exertion through a cultural journey. Thus, we build a digital twin of a university campus located in a region with a rich dragon boat racing tradition. Coupled with three paddling techniques that are enabled by either commercial controllers or physical paddle controllers with haptic feedback, diversified users can engage in realistic rowing experiences. Our results demonstrate that by integrating resistance into the paddle controls, users could simulate the physical effort of dragon boat racing, promoting a deeper understanding and appreciation of this cultural heritage.

cs.MM↗

arXiv2024

Towards AI-Architecture Liberty: A Comprehensive Survey on Design and Generation of Virtual Architecture by Deep Learning

3D shape generation techniques leveraging deep learning have garnered significant interest from both the computer vision and architectural design communities, promising to enrich the content in the virtual environment. However, research on virtual architectural design remains limited, particularly regarding designer-AI collaboration and deep learning-assisted design. In our survey, we reviewed 149 related articles (81.2% of articles published between 2019 and 2023) covering architectural design, 3D shape techniques, and virtual environments. Through scrutinizing the literature, we first identify the principles of virtual architecture and illuminate its current production challenges, including datasets, multimodality, design intuition, and generative frameworks. We then introduce the latest approaches to designing and generating virtual buildings leveraging 3D shape generation and summarize four characteristics of various approaches to virtual architecture. Based on our analysis, we expound on four research agendas, including agency, communication, user consideration, and integrating tools. Additionally, we highlight four important enablers of ubiquitous interaction with immersive systems in deep learning-assisted architectural generation. Our work contributes to fostering understanding between designers and deep learning techniques, broadening access to designer-AI collaboration. We advocate for interdisciplinary efforts to address this timely research topic, facilitating content designing and generation in the virtual environment.

cs.HC↗

arXiv2024

Towards Massive Interaction with Generalist Robotics: A Systematic Review of XR-enabled Remote Human-Robot Interaction Systems

The rising interest of generalist robots seek to create robots with versatility to handle multiple tasks in a variety of environments, and human will interact with such robots through immersive interfaces. In the context of human-robot interaction (HRI), this survey provides an exhaustive review of the applications of extended reality (XR) technologies in the field of remote HRI. We developed a systematic search strategy based on the PRISMA methodology. From the initial 2,561 articles selected, 100 research papers that met our inclusion criteria were included. We categorized and summarized the domain in detail, delving into XR technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (MR), and their applications in facilitating intuitive and effective remote control and interaction with robotic systems. The survey highlights existing articles on the application of XR technologies, user experience enhancement, and various interaction designs for XR in remote HRI, providing insights into current trends and future directions. We also identified potential gaps and opportunities for future research to improve remote HRI systems through XR technology to guide and inform future XR and robotics research.

cs.HC↗

arXiv2024

APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPT

Recent research has highlighted the potential of LLM applications, like ChatGPT, for performing label annotation on social computing text. However, it is already well known that performance hinges on the quality of the input prompts. To address this, there has been a flurry of research into prompt tuning -- techniques and guidelines that attempt to improve the quality of prompts. Yet these largely rely on manual effort and prior knowledge of the dataset being annotated. To address this limitation, we propose APT-Pipe, an automated prompt-tuning pipeline. APT-Pipe aims to automatically tune prompts to enhance ChatGPT's text classification performance on any given dataset. We implement APT-Pipe and test it across twelve distinct text classification datasets. We find that prompts tuned by APT-Pipe help ChatGPT achieve higher weighted F1-score on nine out of twelve experimented datasets, with an improvement of 7.01% on average. We further highlight APT-Pipe's flexibility as a framework by showing how it can be extended to support additional tuning mechanisms.

cs.CL↗

arXiv2023

A Study of Partisan News Sharing in the Russian invasion of Ukraine

Since the Russian invasion of Ukraine, a large volume of biased and partisan news has been spread via social media platforms. As this may lead to wider societal issues, we argue that understanding how partisan news sharing impacts users' communication is crucial for better governance of online communities. In this paper, we perform a measurement study of partisan news sharing. We aim to characterize the role of such sharing in influencing users' communications. Our analysis covers an eight-month dataset across six Reddit communities related to the Russian invasion. We first perform an analysis of the temporal evolution of partisan news sharing. We confirm that the invasion stimulates discussion in the observed communities, accompanied by an increased volume of partisan news sharing. Next, we characterize users' response to such sharing. We observe that partisan bias plays a role in narrowing its propagation. More biased media is less likely to be spread across multiple subreddits. However, we find that partisan news sharing attracts more users to engage in the discussion, by generating more comments. We then built a predictive model to identify users likely to spread partisan news. The prediction is challenging though, with 61.57% accuracy on average. Our centrality analysis on the commenting network further indicates that the users who disseminate partisan news possess lower network influence in comparison to those who propagate neutral news.

cs.SI↗

arXiv2023

Designing Loving-Kindness Meditation in Virtual Reality for Long-Distance Romantic Relationships

Loving-kindness meditation (LKM) is used in clinical psychology for couples' relationship therapy, but physical isolation can make the relationship more strained and inaccessible to LKM. Virtual reality (VR) can provide immersive LKM activities for long-distance couples. However, no suitable commercial VR applications for couples exist to engage in LKM activities of long-distance. This paper organized a series of workshops with couples to build a prototype of a couple-preferred LKM app. Through analysis of participants' design works and semi-structured interviews, we derived design considerations for such VR apps and created a prototype for couples to experience. We conducted a study with couples to understand their experiences of performing LKM using the VR prototype and a traditional video conferencing tool. Results show that LKM session utilizing both tools has a positive effect on the intimate relationship and the VR prototype is a more preferable tool for long-term use. We believe our experience can inform future researchers.

cs.HC↗

arXiv2023

Ghost Booking as a New Philanthropy Channel: A Case Study on Ukraine-Russia Conflict

The term ghost booking has recently emerged as a new way to conduct humanitarian acts during the conflict between Russia and Ukraine in 2022. The phenomenon describes the events where netizens donate to Ukrainian citizens through no-show bookings on the Airbnb platform. Impressively, the social fundraising act that used to be organized on donation-based crowdfunding platforms is shifted into a sharing economy platform market and thus gained more visibility. Although the donation purpose is clear, the motivation of donors in selecting a property to book remains concealed. Thus, our study aims to explore peer-to-peer donation behavior on a platform that was originally intended for economic exchanges, and further identifies which platform attributes effectively drive donation behaviors. We collect over 200K guest reviews from 16K Airbnb property listings in Ukraine by employing two collection methods (screen scraping and HTML parsing). Then, we distinguish ghost bookings among guest reviews. Our analysis uncovers the relationship between ghost booking behavior and the platform attributes, and pinpoints several attributes that influence ghost booking. Our findings highlight that donors incline to credible properties explicitly featured with humanitarian needs, i.e., the hosts in penury.

cs.CY↗

arXiv2023

Using a virtual reality interview simulator to explore factors influencing people's behavior

Virtual reality interview simulator (VRIS) provides an effective and manageable approach for candidates prone to being very nervous during interviews, yet, the major anxiety-inducing elements remain unknown. During an interview, the anxiety levels, overall experience, and performance of interviewees might be affected by various circumstances. By analyzing electrodermal activity and questionnaire, we investigated the influence of five variables: (I) \textit{Realism}; (II) \textit{Question type}; (III) \textit{Interviewer attitude}; (IV) \textit{Timing}; and (V) \textit{Preparation}. As such, an orthogonal design $L_8(4^1 \times 2^4)$ with eight experiments ($O A_8$ matrix) was implemented, in which 19 college students took part in the experiments. Considering the anxiety, overall experience, and performance of the interviewees, results indicate that \textit{Question type} plays a major role; secondly, \textit{Realism}, \textit{Preparation}, and \textit{Interviewer attitude} all have some degree of influence; lastly, \textit{Timing} have little to no impact. Specifically, professional interview questions elicited a greater degree of anxiety than personal ones among the categories of interview questions. This work contributes to our understanding of anxiety-stimulating factors during job interviews in virtual reality and provides cues for designing future VRIS.

cs.HC↗

arXiv2023

What if we have Meta GPT? From Content Singularity to Human-Metaverse Interaction in AIGC Era

The global metaverse development is facing a "cooldown moment", while the academia and industry attention moves drastically from the Metaverse to AI Generated Content (AIGC) in 2023. Nonetheless, the current discussion rarely considers the connection between AIGCs and the Metaverse. We can imagine the Metaverse, i.e., immersive cyberspace, is the black void of space, and AIGCs can simultaneously offer content and facilitate diverse user needs. As such, this article argues that AIGCs can be a vital technological enabler for the Metaverse. The article first provides a retrospect of the major pitfall of the metaverse applications in 2022. Second, we discuss from a user-centric perspective how the metaverse development will accelerate with AIGCs. Next, the article conjectures future scenarios concatenating the Metaverse and AIGCs. Accordingly, we advocate for an AI-Generated Metaverse (AIGM) framework for energizing the creation of metaverse content in the AIGC era.

cs.HC↗

arXiv2023

One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era

OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demonstrated to be one small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI). Since its official release in November 2022, ChatGPT has quickly attracted numerous users with extensive media coverage. Such unprecedented attention has also motivated numerous researchers to investigate ChatGPT from various aspects. According to Google scholar, there are more than 500 articles with ChatGPT in their titles or mentioning it in their abstracts. Considering this, a review is urgently needed, and our work fills this gap. Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges. Moreover, we present an outlook on how ChatGPT might evolve to realize general-purpose AIGC (a.k.a. AI-generated content), which will be a significant milestone for the development of AGI.

cs.CY↗