Soft floating robots (SFRs) represent a shift from rigid machines, offering gravity-defying, compliant, and tactile embodiments for indoor cohabitation. However, their development remains fragmented across isolated prototypes, lacking a coherent design vocabulary. Without a systematic understanding of their interactional capabilities, designers struggle to leverage SFRs’ unique affordances, and these systems often remain limited to novelty applications that are difficult to integrate into everyday life. To address this, we propose a design space for interaction with SFRs. Informed by an exploratory study with 12 experts from HCI, Design, and Robotics, we identify ten design dimensions spanning physical, interactive, and behavioral properties, along with a range of application scenarios. We further present proof-of-concept design examples to demonstrate how this design space can support diverse interaction possibilities. This work contributes a structured framework for understanding and designing interactions with SFRs, supporting their integration into everyday indoor environments.

Cross-disciplinary teams increasingly work with high-dimensional scientific datasets, yet fragmented toolchains and limited support for shared exploration hinder collaboration. Prior immersive visualization & analytics research has emphasized individual interaction, leaving open how multi-user collaboration can be supported at scale. To fill this critical gap, we conduct semi-structured interviews with 20 domain experts from diverse academic, government, and industry backgrounds. Using deductive–inductive hybrid thematic analysis, we identify four collaboration-focused themes: workflow challenges, adoption perceptions, prospective features, and anticipated usability and ethical risks. These findings show how current ecosystems disrupt coordination and shared understanding, while highlighting opportunities for effective multi-user engagement. Our study contributes empirical insights into collaboration practices for high-dimensional scientific data visualization & analysis, offering design implications to enhance coordination, mutual awareness, and equitable participation in next-generation collaborative immersive platforms. These contributions point toward future environments enabling distributed, cross-device teamwork on high-dimensional scientific data.

With large language models (LLMs) on the rise, in-game interactions are shifting from rigid commands to natural conversations. However, the impacts of LLMs on player performance and game experience remain underexplored. This work explores LLM's role as a co-builder during gameplay, examining its impact on task performance, usability, and player experience. Using Minecraft as a sandbox, we present an LLM-assisted interface that engages players through natural language, aiming to facilitate creativity and simplify complex gaming commands. We conducted a mixed-methods study with 30 participants, comparing LLM-assisted and command-based interfaces across simple and complex game tasks. Quantitative and qualitative analyses reveal that the LLM-assisted interface significantly improves player performance, engagement, and overall game experience. Additionally, task complexity has a notable effect on player performance and experience across both interfaces. Our findings highlight the potential of LLM-assisted interfaces to revolutionize virtual experiences, emphasizing the importance of balancing intuitiveness with predictability, transparency, and user agency in AI-driven, multimodal gaming environments.

Social virtual reality (VR) has the potential to replace conventional online social media by offering quasi-real-world social experiences. As such, it has been extensively examined by the research community. However, existing studies fall short of providing a comprehensive understanding of how different aspects of social VR platforms interact to affect user experience. Motivated by this limitation, we conduct a user study with Oculus Quest 2 headsets and dissect the user experience on five social VR platforms. We evenly and randomly divide 42 participants into short-term (spending 10-30 minutes/platform) and long-term (spending at least 120 minutes/platform) groups. Besides employing surveys and interviews, we measure the frame rate and resolution of these platforms and explore how various factors interplay to influence the user experience of social VR. Our findings reveal that the frame rate, resolution, and interactive events of social VR platforms have a more significant impact on the experience of long-term users compared to short-term users. The scalability limitations of these platforms, as evidenced by decreased frame rates with the increasing number of concurrent users, result in an increased prevalence of motion sickness among long-term users, negatively impacting their overall experience. Moreover, the absence of highly interactive events also deteriorates their overall experience, and the low resolution combined with the lack of interactive events further decreases their sense of social presence. Additionally, our study demonstrates several common limitations negatively affecting the experience of both long-term and short-term users. For example, the harassment prevention mechanisms on all five platforms are inadequate, and being harassed has a detrimental effect on users' overall experience and sense of social presence. The avatar embodiment of investigated platforms has limited contribution to users' sense of social presence, mainly due to the lack of realism and full-body tracking. Our findings call for more research in scalability support, motion sickness relief, interactive event design, harassment prevention, and avatar development for improving social VR platforms in the future.

Among creative professionals, Generative Artificial Intelligence (GenAI) has sparked excitement over its capabilities and fear over unanticipated consequences. How does GenAI impact User Experience Design (UXD) practice, and are fears warranted? We interviewed 20 UX Designers, with diverse experience and across companies (startups to large enterprises). We probed them to characterize their practices, and sample their attitudes, concerns, and expectations. We found that experienced designers are confident in their originality, creativity, and empathic skills, and find GenAI’s role as assistive. They emphasized the unique human factors of “enjoyment” and “agency”, where humans remain the arbiters of “AI alignment’’. However, skill degradation, job replacement, and creativity exhaustion can adversely impact junior designers. We discuss implications for human-GenAI collaboration, specifically copyright and ownership, human creativity and agency, and AI literacy and access. Through the lens of responsible and participatory AI, we contribute a deeper understanding of GenAI fears and opportunities for UXD.

Social Virtual Reality (VR) is regarded as one of the most popular VR applications since it transcends geographical barriers, allowing users to interact in simulated environments for various purposes. Despite its promising prospects, there is a growing concern about the harassment issue due to the immersive nature of social VR compared to other online social environments. Existing protections against harassment in social VR are highly limited in terms of practical effectiveness. The deficiency of studies toward understanding and preventing harassment in social VR further complicates the regulation and intervention efforts of social VR platforms in such situations. To address these challenges, we, in this paper, quantitatively investigate human interaction behaviors in social VR. More specifically, we first build a customized platform based on Mozilla Hubs, a popular social VR platform, to collect data about users’ social interaction behaviors involving harassment instances. A subsequent analysis of the collected dataset SAHARA (Social interAction beHAviors in vR with hArassment) reveals that the task of online harassment detection in social VR is complicated since it depends on not only users’ actions but also their spatial and temporal relationships. To accurately discern harassment, we propose a novel framework HardenVR (HA-Rassment DEtectioN framework for social VR). As a context-aware harassment detection framework, HardenVR employs a transformer-based model to capture relative poses and learn users’ hand actions in 6-DOF (Degree-of-Freedom). Meanwhile, multiple mechanisms, including the extra attention mechanism, distance-aware clustering method, and the sliding window, have been introduced into the model to handle challenges of data imbalance, over-fitting, and continuous detection. The design of HardenVR aims to achieve the balance between accuracy, efficiency, and cost-effectiveness for the task of harassment detection. As a starting point, HardenVR successfully learns pose information as the context to identify harassment and the experiment results show its detection accuracy as high as 98.26%.

Social virtual reality (VR) allows multiple remote users to interact in a shared space, unveiling new possibilities for communication in immersive environments. Mediascape XR presents a social VR experience that teleports 3D representations of remote users, using volumetric video, to a virtual museum. It enables visitors to interact with cultural heritage artifacts while allowing social interactions in real time between them. The application is designed following a human-centered approach, enabling an interactive, educating, and entertaining experience.

Cake customization services allow clients to collaboratively personalize cakes with pastry chefs. However, remote (e.g., email) and in-person co-design sessions are prone to miscommunication, due to natural restrictions in visualizing cake size, decoration, and celebration context. This paper presents the design, implementation, and expert evaluation of a social VR application (CakeVR) that allows a client to remotely co-design cakes with a pastry chef, through real-time realistic 3D visualizations. Drawing on expert semi-structured interviews (4 clients, 5 pastry chefs), we distill and incorporate 8 design requirements into our CakeVR prototype. We evaluate CakeVR with 10 experts (6 clients, 4 pastry chefs) using cognitive walkthroughs, and find that it supports ideation and decision making through intuitive size manipulation, color/flavor selection, decoration design, and custom celebration theme fitting. Our findings provide recommendations for enabling co-design in social VR and highlight CakeVR’s potential to transform product design communication through remote interactive and immersive co-design.

Virtual environments (VEs) can create collaborative and social spaces, which are increasingly important in the face of remote work and travel reduction. Recent advances, such as more open and widely available platforms, create new possibilities to observe and analyse interaction in VEs. Using a custom instrumented build of Mozilla Hubs to measure position and orientation, we conducted an academic workshop to facilitate a range of typical workshop activities. We analysed social interactions during a keynote, small group breakouts, and informal networking/hallway conversations. Our mixed-methods approach combined environment logging, observations, and semi-structured interviews. The results demonstrate how small and large spaces influenced group formation, shared attention, and personal space, where smaller rooms facilitated more cohesive groups while larger rooms made small group formation challenging but personal space more flexible. Beyond our findings, we show how the combination of data and insights can fuel collaborative spaces’ design and deliver more effective virtual workshops.

We all enjoy watching movies together. However, this is not always possible if we live apart. While we can remotely share our screens, the experience differs from being together. We present a social Virtual Reality (VR) system that captures, reconstructs, and transmits multiple users’ volumetric representations into a commercially produced 3D virtual movie, so they have the feeling of “being there” together. We conducted a 48-user experiment where we invited users to experience the virtual movie either using a Head Mounted Display (HMD) or using a 2D screen with a game controller. In addition, we invited 14 VR experts to experience both the HMD and the screen version of the movie and discussed their experiences in two focus groups. Our results showed that both end-users and VR experts found that the way they navigated and interacted inside a 3D virtual movie was novel. They also found that the photorealistic volumetric representations enhanced feelings of co-presence. Our study lays the groundwork for future interactive and immersive VR movie co-watching experiences.

In recent years, artists and communities have expressed the desire to work with tools that facilitate co-creation and allow distributed community performances. These performances can be spread over several physical stages, connecting them on real-time towards a single experience with the audience distributed along them. This enables a wider remote audience consuming the performance through their own devices, and even grants the participation of remote users in the show. In this paper we introduce the Co-creation Stage, a web-based tool that allows managing heterogeneous content sources, with a particular focus on live and on-demand media, across several distributed devices. The Co-creation Stage is part of the toolset developed in the Traction H2020 project which enables community performing art shows, where professional artists and non-professional participants perform together from different stages and locations. Here we present the design process, the architecture and the main functionalities of the tool as well as the results of the first user evaluation with Opera houses and artists.

Virtual Reality (VR) and Augmented Reality (AR) applications have seen a drastic increase in commercial popularity. Different representations have been used to create 3D reconstructions for AR and VR. Point clouds are one such representation characterized by their simplicity and versatility, making them suitable for real time applications, such as reconstructing humans for social virtual reality. In this study, we evaluate how the visual quality of digital humans, represented using point clouds, is affected by compression distortions. We compare the performance of the upcoming point cloud compression standard against an octree-based anchor codec. Two different VR viewing conditions enabling 3- and 6 degrees of freedom are tested, to understand how interacting in the virtual space affects the perception of quality. To the best of our knowledge, this is the first work performing user quality evaluation of dynamic point clouds in VR; in addition, contributions of the paper include quantitative data and empirical findings. Results highlight how perceived visual quality is affected by the tested content, and how current data sets might not be sufficient to comprehensively evaluate compression solutions. Moreover, shortcomings in how point cloud encoding solutions handle visually-lossless compression are discussed.

Millions of photos are shared online daily, but the richness of interaction compared with face-to-face (F2F) sharing is still missing. While this may change with social Virtual Reality (socialVR), we still lack tools to measure such immersive and interactive experiences. In this paper, we investigate photo sharing experiences in immersive environments, focusing on socialVR. Running context mapping (N=10), an expert creative session (N=6), and an online experience clustering questionnaire (N=20), we develop and statistically evaluate a questionnaire to measure photo sharing experiences. We then ran a controlled, within-subject study (N=26 pairs) to compare photo sharing under F2F, Skype, and Facebook Spaces. Using interviews, audio analysis, and our questionnaire, we found that socialVR can closely approximate F2F sharing. We contribute empirical findings on the immersiveness differences between digital communication media, and propose a socialVR questionnaire that can in the future generalize beyond photo sharing.

In this paper, we describe a user study in which pairs of users watch a video trailer and interact with each other, using two social Virtual Reality (sVR) systems, as well as in a face-to-face condition. The sVR systems are: Facebook Spaces, based on puppet-like customized avatars, and a video-based sVR system using photo-realistic virtual user representations. We collect subjective and objective data to analyze users' Quality of Experience (QoE) and compare their interaction in VR to that observed during the real-life scenario. Our results show that the experience delivered by the video-based sVR system is comparable with real-life settings, while the puppet-based avatars limit the perceived quality of the interaction. Our protocol for QoE assessment is fully documented to allow replication in similar experiments.