Scaling Techniques for Exocentric Navigation Interfaces in Multiscale Virtual Environments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Navigating multiscale virtual environments necessitates an interaction method to travel across different levels of scale (LoS). Prior research has studied various techniques that enable users to seamlessly adjust their scale to navigate between different LoS based on specific user contexts. We introduce a scroll-based scale control method optimized for exocentric navigation, targeted at scenarios where speed and accuracy in continuous scaling are crucial. We pinpoint the challenges of scale control in settings with multiple LoS and evaluate how distinct designs of scaling techniques influence navigation performance and usability. Through a user study, we investigated two pivotal elements of a scaling technique: the input method and the scaling center. Our findings indicate that our scroll-based input method significantly reduces task completion time and error rate and enhances efficiency compared to the most frequently used bi-manual method. Moreover, we found that the choice of scaling center affects the ease of use of the scaling method, especially when paired with specific input methods.
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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 | 0.001 | 0.001 |
| 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 it