Eye Caramba: Gaze-based Assistance for Virtual Reality Aiming and Throwing Tasks in Games
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
Gaze-based interaction in Virtual Reality (VR) has been attracting attention recently due to rapid advances in eye tracking technology in head-mounted displays. Since gazes are a natural and intuitive interaction modality for human beings, gaze-based interaction could enhance player experience in immersive VR games. Aiming assistance is a common feature in games to balance difficulty for different player skills. Previous work has investigated different aim assistance approaches and identified various shortcomings. We hypothesize that “bullet magnetism” is a promising technique for VR and could be enhanced by extending its functionality through players’ gazes. In this paper, we present a gaze-based aiming assistance approach and propose a study design to evaluate its performance and player experience in a “Mexican-style” VR first-person shooter game.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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