Bibliographic record
Abstract
The creation of novel 3D content is one of the major bottlenecks of modern computer graphics. Commercial modeling systems are targeted toward expert users and require significant time, expertise and artistic talent to generate 3D shapes. Hence, much of the emphasis in recent research is on simplifying model creation. One approach is to provide simpler interfaces, such as sketching tools. Another recent trend focuses on reuse of existing models by providing robust editing tools. Most of those tools still require the user to have modeling expertise and nonnegligible artistic ability. In this talk I will review some recent trends in providing simple modeling interfaces. I will then demonstrate that by narrowing the scope of the problem, and focusing on modeling within a specific set of models, it is possible to develop a true "modeling for dummies" interface which does not require any modeling expertise or talent. Despite its simplicity the interface allows for creation of rich geometric content within a matter of minutes. The proposed modeling system, Shuffler, operates on sets of models that have a similar part-based structure. Example sets include quadrupeds, humans, chairs, and airplanes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".