Rapid forgetting prevented by retrospective attention cues.
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
Recent studies have demonstrated that memory performance can be enhanced by a cue which indicates the item most likely to be subsequently probed, even when that cue is delivered seconds after a stimulus array is extinguished. Although such retro-cuing has attracted considerable interest, the mechanisms underlying it remain unclear. Here, we tested the hypothesis that retro-cues might protect an item from degradation over time. We employed two techniques that previously have not been deployed in retro-cuing tasks. First, we used a sensitive, continuous scale for reporting the orientation of a memorized item, rather than binary measures (change or no change) typically used in previous studies. Second, to investigate the stability of memory across time, we also systematically varied the duration between the retro-cue and report. Although accuracy of reporting uncued objects rapidly declined over short intervals, retro-cued items were significantly more stable, showing negligible decline in accuracy across time and protection from forgetting. Retro-cuing an object's color was just as advantageous as spatial retro-cues. These findings demonstrate that during maintenance, even when items are no longer visible, attention resources can be selectively redeployed to protect the accuracy with which a cued item can be recalled over time, but with a corresponding cost in recall for uncued items.
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 | 0.001 | 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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