Influencer: Empowering Everyday Users in Creating Promotional Posts via AI-infused Exploration and Customization
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
Figure 1: A design novice uses Infuencer to ideate and make promotional posts to promote their homemade juice.Infuencer has the following core features: (A) The user can input a topic via a text block and explores the related images and captions in three dimensions.(B) Context-aware exploration is supported which updates the image and caption recommendation by dragging a brand/product image or message to the initial image and caption recommendation.(C) Various materials (i.e., image and text) can be fexibly fused to make a new image or caption.(D) Infuencer allows the user to not only easily create harmonious promotional posts but also quickly obtain multiple post alternatives.Steps in (A), (B), and (C) can be fexibly combined or skipped; as soon as the user fnds satisfed image and/or caption, they can go to (D) for post generation.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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