A Reusable Scripting Engine for Automating Cinematics and Cut-Scenes in Video 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
Storytelling can play a critical role in the success of modern video games. Unfortunately, it can often be quite difficult for storytellers to directly craft content for games, typically requiring them to work with programmers to implement story elements. This needlessly complicates the development process, straining scarce resources while potentially hampering creativity and story quality at the same time. As a result, supports and tools are necessary to enable storytellers to generate story content for games directly, with minimal programming or programmer assistance required, if any. This paper introduces a Reusable Scripting Engine to automate the generation of cinematics and cut-scenes in video games. This approach allows storytellers to provide their stories in a well-defined, structured format, which is then interpreted by our engine, along with supplemental graphic and audio content, to produce an animated presentation of the story in an automated fashion. This paper presents the design of our Reusable Scripting Engine, and discusses a prototype implementation of this design, as well as initial experiences with using this prototype system to date.
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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 | 0.001 |
| 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 it