arXiv subjects

Hai-Ning Liang

Publications and source records attributed to Hai-Ning Liang.

At least 19 recordsLinked to original sources

arXiv2026

AppLooper: An Agentic Application Engineering Loop for Accountable Release with Virtual-User Feedback

Much existing research on coding agents organizes application development as an iterative loop of requirement interpretation, implementation, tool execution, evaluation, and repair. As these loops run longer, requirements may drift; users may lose awareness of the current state and rationale for changes; and generated applications may remain insufficiently grounded in target users' contexts and needs. Application engineering therefore requires a mechanism connecting owner intent, target-user experience, development changes, and responsibility for release. We present AppLooper, a human--coding-agent--virtual-user application engineering loop for accountable release. An application owner confirms frozen requirements, supplies feedback, inspects candidates, and retains final release authority. A development agent produces and revises versioned candidates. A virtual-user agent cohort executes interface scenarios grounded in target users and contexts of use. Besides, an owner-intent simulation agent retests only requirements, constraints, and feedback explicitly confirmed by the owner, abstaining when evidence is insufficient. A testing agent performs read-only developmental checks by reproducing reported failures, running existing regression tests, and exercising the current candidate through its browser interface. The orchestration layer groups the resulting findings and routes them into development revision, targeted retesting, and owner inspection. AppLooper binds requirements, feedback sources, interface targets, development changes, retesting outcomes, owner interactions, and release decisions to specific versions. It thereby extends sustained coding-agent iteration into a traceable and reviewable lifecycle in which humans retain final responsibility for release. Source code is available at https://github.com/ZihongHe/applooper.

cs.HC↗

arXiv2026

Conflict Resolution Strategies for Co-manipulation of Virtual Objects Under Non-disjoint Conditions

Virtual Reality (VR) co-manipulation enables multiple users to collaboratively interact with shared virtual objects. However, existing research treats objects as monolithic entities, overlooking scenarios where users need to manipulate different sub-components simultaneously. This work addresses conflict resolution when users select overlapping vertices (non-disjoint sets) during co-manipulation. We present a comprehensive framework comprising preventive strategies (Object-level and Action-level Restrictions) and reactive strategies (computational conflict resolution). Through two user studies with 76 participants (38 pairs), we evaluated these approaches in collaborative wireframe editing tasks. Study 1 identified Averaging as the optimal computational method, balancing task efficiency with user experience. Study 2 highlighted that Action-level Restriction, which permits overlapping selections but restricts concurrent identical operations, achieved better performance compared to exclusive object locking. Reactive strategies using averaging provided smooth collaboration for experienced users, while second-user priority enabled quick corrections. Our findings indicate that optimal strategy selection depends on task requirements, user expertise, and collaboration patterns. Based on the findings, we provide design implications for developing VR collaboration systems that support flexible sub-components manipulation while maintaining collaborative awareness and minimizing conflicts.

cs.HC↗

arXiv2026

FlexiCamAR: Enhancing Everyday Camera Interactions on AR Glasses with a Flexible Additional Viewpoint

The recent emergence and popularity of consumer-grade augmented reality (AR) glasses from major technology companies highlight their potential to become the next daily computing platform. A dominant design trend in this context is the integration of a front-facing camera to deliver a first-person perspective. While this approach is intuitive, there is limited evidence that it is optimal (or sufficient) for supporting users in daily tasks. This paper explores a more effective camera interaction technique for AR glasses, which we term ``FlexiCamAR." This novel method aims to enhance both efficiency and the range of applications for AR glasses by offering flexible and comfortable secondary camera viewpoints. To investigate the applicability and usability of this approach, we developed a ring camera prototype that can be attached to users' fingers. We then conducted a user study with 12 participants, comparing FlexiCamAR against the baseline, a traditional front-facing AR camera setup, across two common tasks: taking photos and scanning QR codes. Our findings show that FlexiCamAR significantly reduces physical load. We also explore potential scenarios where the additional viewpoint afforded by FlexiCamAR proves valuable, such as capturing low-angle perspectives or navigating confined spaces. Participant feedback further suggests strong potential for additional applications, including selfie taking, video conferencing, and object scanning. Overall, FlexiCamAR presents a novel interaction approach that can serve as a powerful supplement or alternative to the first-person perspective, significantly improving the adaptability of AR glasses for everyday use.

cs.HC↗

arXiv2026

Observable Social Life Spaces: Exploring User Interpretations of agent-side life context in human-agent interaction

Many AI agents are organized around instrumental "command-execution" interactions, where users primarily encounter agents through task requests and responses. Recent work on generative agents and agent life worlds has drawn attention to agents that maintain social contexts beyond direct user commands. In this paper, we study how observable social life spaces shape users' subjective experience, relational interpretations, and perceived equality during human-agent interaction. We introduce the \textit{Observable Social Life Spaces} paradigm, where agents inhabit a continuous virtual environment, engage in daily activities, and form social relationships that users can directly observe. Through an exploratory mixed-methods study ($N=24$), we found that the Observable condition yielded higher perceived-equality ratings and more frequent equality-related role descriptions than the Baseline and Unobservable conditions, but participant-level analysis suggests that the quantitative effect should be interpreted cautiously. We discuss perceived equality as a user-perception signal shaped by this design, with attention to boundary conditions including visual richness, novelty, and person-like attribution from visible agent cues.

cs.HC↗

arXiv2026

Tap-to-Adapt: Learning User-Aligned Response Timing for Speech Agents

Response timing judgment is a critical component of interactive speech agents. Although there exists substantial prior work on turn modeling and voice wake-up, there is a lack of research on response timing judgments continuously aligned with user intent. To address this, we propose the Tap-to-Adapt framework, which enables users to naturally activate or interrupt the agent via tap interactions to construct online learning labels for response timing models. Under this framework, Dilated TCN and a sequential replay strategy play significant roles, as demonstrated through data-driven experiments and user studies. Additionally, we develop an evaluation and continuous data mining system tailored for the Tap-to-Adapt framework, through which we have collected approximately 20,000 samples from the user studies involving 20 participants.

cs.HC↗

arXiv2026

ScaleFree: Dynamic KDE for Multiscale Point Cloud Exploration in VR

We present ScaleFree, a GPU-accelerated adaptive Kernel Density Estimation (KDE) algorithm for scalable, interactive multiscale point cloud exploration. With this technique, we cater to the massive datasets and complex multiscale structures in advanced scientific computing, such as cosmological simulations with billions of particles. Effective exploration of such data requires a full 3D understanding of spatial structures, a capability for which immersive environments such as VR are particularly well suited. However, simultaneously supporting global multiscale context and fine-grained local detail remains a significant challenge. A key difficulty lies in dynamically generating continuous density fields from point clouds to facilitate the seamless scale transitions: while KDE is widely used, precomputed fields restrict the accuracy of interaction and omit fine-scale structures, while dynamic computation is often too costly for real-time VR interaction. We address this challenge by leveraging GPU acceleration with k-d-tree-based spatial queries and parallel reduction within a thread group for on-the-fly density estimation. With this approach, we can recalculate scalar fields dynamically as users shift their focus across scales. We demonstrate the benefits of adaptive density estimation through two data exploration tasks: adaptive selection and progressive navigation. Through performance experiments, we demonstrate that ScaleFree with GPU-parallel implementation achieves orders-of-magnitude speedups over sequential and multi-core CPU baselines. In a controlled experiment, we further confirm that our adaptive selection technique improves accuracy and efficiency in multiscale selection tasks.

cs.HC↗

arXiv2026

The Perceptual Cost of Passthrough: How Video See-Through HMDs Degrade Human Visual Perception of Acuity, Contrast, and Color

Video see-through (VST) technology aims to seamlessly blend the virtual and physical worlds by reconstructing reality through cameras. However, while manufacturers promise high perceptual fidelity, it remains unclear how closely recent commercial VST systems preserve basic visual functions across environmental conditions. In this work, we present an end-to-end perceptual benchmark for three popular VST headsets: Apple Vision Pro, Meta Quest 3, and Meta Quest Pro. Using adapted psychophysical measures, we evaluated participants' visual acuity, contrast sensitivity, and color vision under both normal and low-light conditions, with naked-eye vision as the reference. Our results show measurable gaps between VST and naked-eye performance, especially for visual acuity and contrast sensitivity in low-light environments. By mapping these perceptual gaps across devices, visual functions, and lighting levels, this work provides a practical benchmark for current commercial VST capabilities and highlights where experience design or device optimization may need to compensate for perceptual loss.

cs.HC↗

arXiv2026

Resolution deficits drive simulator sickness and compromise reading performance in virtual environments

Extended reality (XR) is evolving into a general-purpose computing platform, yet its adoption for productivity is hindered by visual fatigue and simulator sickness. While these symptoms are often attributed to latency or motion conflicts, the precise impact of textual clarity on physiological comfort remains undefined. Here we show that sub-optimal effective resolution, the clarity that reaches the eye after the full display-optics-rendering pipeline, is a primary driver of simulator sickness during reading tasks in both virtual reality and video see-through environments. By systematically manipulating end-to-end effective resolution on a unified logMAR scale, we measured reading psychophysics and sickness symptoms in a controlled within-subjects study. We find that reading performance and user comfort degrade exponentially as resolution drops below 0 logMAR (normal visual acuity). Notably, our results reveal 0 logMAR as a key physiological tipping point: resolutions better than this threshold yield naked-eye-level performance with minimal sickness, whereas poorer resolutions trigger rapid, non-linear increases in nausea and oculomotor strain. These findings suggest that the cognitive and perceptual effort required to resolve blurry text directly compromises user comfort, establishing human-eye resolution as a critical baseline for the design of future ergonomic XR systems.

cs.HC↗

arXiv2025

Say it or AI it: Evaluating Hands-Free Text Correction in Virtual Reality

Text entry in Virtual Reality (VR) is challenging, even when accounting for the use of controllers. Prior work has tackled this challenge head-on, improving the efficiency of input methods. These techniques have the advantage of allowing for relatively straightforward text correction. However, text correction without the use of controllers is a topic that has not received the same amount of attention, even though it can be desirable in several scenarios, and can even be the source of frustration. Large language models have been adopted and evaluated as a corrective methodology, given their high power for predictions. Nevertheless, their predictions are not always correct, which can lead to lower usability. In this paper, we investigate whether, for text correction in VR that is hands-free, the use of AI could surpass in terms of usability and efficiency. We observed better usability for AI text correction when compared to voice input.

cs.HC↗

arXiv2025

From Adaptation to Intelligence: A Systematic Review of Data, Strategies, and Impact in Personalized VR

As virtual reality (VR) systems advance, they are increasingly expected to adapt intelligently to individual users' states, abilities, and preferences. While prior research has examined user-state sensing and adaptive interaction design in VR, existing reviews typically address these aspects in isolation. In this paper, we examine the growing body of research on personalization in VR, with a particular focus on how user data collected during immersion is used to drive adaptive strategies that tailor the experience and enhance engagement, performance, or other specific goals. We synthesize findings from studies that employ adaptive techniques across diverse application domains and summarize a five-stage conceptual framework that unifies adaptive mechanisms across domains. Our analysis reveals emerging trends, including the integration of multimodal sensors, the transition from purely reactive to hybrid adaptation systems, and the adoption of artificial intelligence approaches. Finally, we identify key challenges related to data, modeling, and evaluation, and outline future research directions toward more effective and user-centered VR systems.

cs.HC↗

arXiv2025

Exploring the Feasibility of Gaze-Based Navigation Across Path Types

Gaze input, as a modality inherently conveying user intent, offers intuitive and immersive experiences in extended reality (XR). With eye-tracking now being a standard feature in modern XR headsets, gaze has been extensively applied to tasks such as selection, text entry, and object manipulation. However, gaze based navigation despite being a fundamental interaction task remains largely underexplored. In particular, little is known about which path types are well suited for gaze navigation and under what conditions it performs effectively. To bridge this gap, we conducted a controlled user study evaluating gaze-based navigation across three representative path types: linear, narrowing, and circular. Our findings reveal distinct performance characteristics and parameter ranges for each path type, offering design insights and practical guidelines for future gaze-driven navigation systems in XR.

cs.HC↗

arXiv2025

CountingFruit: Language-Guided 3D Fruit Counting with Semantic Gaussian Splatting

Accurate 3D fruit counting in orchards is challenging due to heavy occlusion, semantic ambiguity between fruits and surrounding structures, and the high computational cost of volumetric reconstruction. Existing pipelines often rely on multi-view 2D segmentation and dense volumetric sampling, which lead to accumulated fusion errors and slow inference. We introduce FruitLangGS, a language-guided 3D fruit counting framework that reconstructs orchard-scale scenes using an adaptive-density Gaussian Splatting pipeline with radius-aware pruning and tile-based rasterization, enabling scalable 3D representation. During inference, compressed CLIP-aligned semantic vectors embedded in each Gaussian are filtered via a dual-threshold cosine similarity mechanism, retrieving Gaussians relevant to target prompts while suppressing common distractors (e.g., foliage), without requiring retraining or image-space masks. The selected Gaussians are then sampled into dense point clouds and clustered geometrically to estimate fruit instances, remaining robust under severe occlusion and viewpoint variation. Experiments on nine different orchard-scale datasets demonstrate that FruitLangGS consistently outperforms existing pipelines in instance counting recall, avoiding multi-view segmentation fusion errors and achieving up to 99.7% recall on Pfuji-Size_Orch2018 orchard dataset. Ablation studies further confirm that language-conditioned semantic embedding and dual-threshold prompt filtering are essential for suppressing distractors and improving counting accuracy under heavy occlusion. Beyond fruit counting, the same framework enables prompt-driven 3D semantic retrieval without retraining, highlighting the potential of language-guided 3D perception for scalable agricultural scene understanding.

cs.CV↗

arXiv2025

No More Head-Turning: Exploring Passthrough Techniques for Addressing Rear Interruptions from the Front in VR

Virtual reality (VR) users often encounter interruptions, posing challenges to maintaining real-world awareness during immersive experiences. The Passthrough feature in VR headsets allows users to view their physical surroundings without removing the headset. However, when interruptions come from the rear, users need to turn their heads to see the real world, which can lead to negative experiences in VR. Study 1, conducted through semi-structured interviews involving 13 participants, found that users are less likely to use Passthrough for rear interruptions due to large head-turning movements, which cause inconvenience, increase the risk of motion sickness, and reduce the experience. Building on these findings, we introduced three Passthrough techniques in Study 2 for displaying the rear view in front of the user: Full Rear Passthrough + Pause (FRPP), Rear Passthrough Window (RPW), and Rear Passthrough AR (RPAR). Compared to the Baseline method that requires head-turning, all three systems reduced physical and temporal demands, alleviated disorientation caused by motion sickness, and provided a better user experience for managing rear interruptions. Among these, FRPP and RPAR were the most preferred. These findings provide valuable insights for future VR design, emphasizing the need for solutions that effectively manage rear interruptions while maintaining user comfort and experience.

cs.HC↗

arXiv2024

Investigating Creation Perspectives and Icon Placement Preferences for On-Body Menus in Virtual Reality

On-body menus present a novel interaction paradigm within Virtual Reality (VR) environments by embedding virtual interfaces directly onto the user's body. Unlike traditional screen-based interfaces, on-body menus enable users to interact with virtual options or icons visually attached to their physical form. In this paper, We investigated the impact of the creation process on the effectiveness of on-body menus, comparing first-person, third-person, and mirror perspectives. Our first study ($N$ = 12) revealed that the mirror perspective led to faster creation times and more accurate recall compared to the other two perspectives. To further explore user preferences, we conducted a second study ($N$ = 18) utilizing a VR system with integrated body tracking. By combining distributions of icons from both studies ($N$ = 30), we confirmed significant preferences in on-body menu placement based on icon category (e.g., Social Media icons were consistently placed on forearms). We also discovered associations between categories, such as Leisure and Social Media icons frequently co-occurring. Our findings highlight the importance of the creation process, uncover user preferences for on-body menu organization, and provide insights to guide the development of intuitive and effective on-body interactions within virtual environments.

cs.HC↗

arXiv2024

Experimental Analysis of Freehand Multi-Object Selection Techniques in Virtual Reality Head-Mounted Displays

Object selection is essential in virtual reality (VR) head-mounted displays (HMDs). Prior work mainly focuses on enhancing and evaluating techniques for selecting a single object in VR, leaving a gap in the techniques for multi-object selection, a more complex but common selection scenario. To enable multi-object selection, the interaction technique should support group selection in addition to the default pointing selection mode for acquiring a single target. This composite interaction could be particularly challenging when using freehand gestural input. In this work, we present an empirical comparison of six freehand techniques, which are comprised of three mode-switching gestures (Finger Segment, Multi-Finger, and Wrist Orientation) and two group selection techniques (Cone-casting Selection and Crossing Selection) derived from prior work. Our results demonstrate the performance, user experience, and preference of each technique. The findings derive three design implications that can guide the design of freehand techniques for multi-object selection in VR HMDs.

cs.HC↗

arXiv2024

Exploring the Impact of Passthrough on VR Exergaming in Public Environments: A Field Study

Sedentary behavior is becoming increasingly prevalent in daily work and study environments. VR exergaming has emerged as a promising solution in these places of work and study. However, private spaces in these environments are not easy, and engaging in VR exergaming in public settings presents its own set of challenges (e.g., safety, social acceptance, isolation, and privacy protection). The recent development of Passthrough functionality in VR headsets allows users to maintain awareness of their surroundings, enhancing safety and convenience. Despite its potential benefits, little is known about how Passthrough could affect user performance and experience and solve the challenges of playing VR exergames in real-world public environments. To our knowledge, this work is the first to conduct a field study in an underground passageway on a university campus to explore the use of Passthrough in a real-world public environment, with a disturbance-free closed room as a baseline. Results indicate that enabling Passthrough in a public environment improves performance without compromising presence. Moreover, Passthrough can increase social acceptance, especially among individuals with higher levels of self-consciousness. These findings highlight Passthrough's potential to encourage VR exergaming adoption in public environments, with promising implications for overall health and well-being.

cs.HC↗

arXiv2024

Enhancement of Co-located Shared VR Experiences: Representing Non-HMD Observers on Both HMD and 2D Screen

Virtual reality (VR) not only allows head-mounted display (HMD) users to immerse themselves in virtual worlds but also to share them with others. When designed correctly, this shared experience can be enjoyable. However, in typical scenarios, HMD users are isolated by their devices, and non-HMD observers lack connection with the virtual world. To address this, our research investigates visually representing observers on both HMD and 2D screens to enhance shared experiences. The study, including five representation conditions, reveals that incorporating observer representation positively impacts both HMD users and observers. For how to design and represent them, our work shows that HMD users prefer methods displaying real-world visuals, while observers exhibit diverse preferences regarding being represented with real or virtual images. We provide design guidelines tailored to both displays, offering valuable insights to enhance co-located shared VR experiences for HMD users and non-HMD observers.

cs.HC↗

arXiv2024

3DStoryline: Immersive Visual Storytelling

Storyline visualization has emerged as an innovative method for illustrating the development and changes in stories across various domains. Traditional approaches typically represent stories with one line per character, progressing from left to right. While effective for simpler narratives, this method faces significant challenges when dealing with complex stories involving multiple characters, as well as temporal and spatial dynamics. In this study, we investigate the potential of immersive environments for enhancing storyline visualizations. We begin by summarizing the key design considerations for effective storyline visualization in virtual reality (VR). Guided by these principles, we develop 3DStoryline, a system that allows users to view and interact with 3D immersive storyline visualizations. To evaluate the effectiveness of 3DStoryline, we conduct a task-based user study, revealing that the system significantly enhances users' comprehension of complex narratives.

cs.HC↗