XRmas: Extended Reality Multi-Agency Spaces for a Magical Remote Christmas
Bibliographic record
Abstract
The COVID-19 pandemic has raised attention toward remote and hybrid communications. Currently, one highly-studied solution lets a remote user use virtual reality (VR) to enter an immersive view of a local space, and local users use augmented reality (AR) to see the remote user's representation and digital contents. Such systems give the remote user a sense of ‘being there’, but we identify two more challenges to address. First, current systems provide remote users with limited agency to control objects and influence the local space. It is necessary to further explore the relationship between users, virtual objects, and physical objects, and how they can play a role in providing richer agency. Second, current systems often try to replicate in-person experiences, but hardly surpass them. We propose XRmas: an AR/VR telepresence system that (1) provides a multi-agency space that allows a remote user to manipulate both virtual and physical objects in a local space, and (2) introduces three family activities in a Christmas context that adopt holographic animation effects to create a ‘magical’ experience that takes users beyond merely the feeling of ‘being there’. We report on preliminary insights from the use of such a system in a remote family communication context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".