Perceptual comparisons induce lasting and generalizing changes to face memory reports
Bibliographic record
Abstract
Humans are often tasked to remember new faces so that they can recognize the faces later in time. Previous studies found that memory reports for basic visual features (e.g., colors and shapes) are susceptible to systematic distortions as a result of comparison with new visual input, especially when the input is perceived as similar to the memory. The current study tested whether this similarity-induced memory bias (SIMB) would also occur with more complex face stimuli. The results showed that faces that are just perceptually encoded into visual working memory as well as retrieved from visual long-term memory are also susceptible to SIMB. Furthermore, once induced, SIMB persisted over time across cues through which the face memory was accessed for memory report. These results demonstrate the generalizability of SIMB to more complex and practically relevant stimuli, and thus, suggest potential real-world implications.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 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".