Learning New Vocabulary Implicitly During Sleep Transfers With Cross-Modal Generalization Into Wakefulness
Bibliographic record
Abstract
New information can be learned during sleep but the extent to which we can access this knowledge after awakening is far less understood. Using a novel Associative Transfer Learning paradigm, we show that, after hearing unknown Japanese words with sounds referring to their meaning during sleep, participants could identify the images depicting the meaning of newly acquired Japanese words after awakening ( N = 22). Moreover, we demonstrate that this cross-modal generalization is implicit, meaning that participants remain unaware of this knowledge. Using electroencephalography, we further show that frontal slow-wave responses to auditory stimuli during sleep predicted memory performance after awakening. This neural signature of memory formation gradually emerged over the course of the sleep phase, highlighting the dynamics of associative learning during sleep. This study provides novel evidence that the formation of new associative memories can be traced back to the dynamics of slow-wave responses to stimuli during sleep and that their implicit transfer into wakefulness can be generalized across sensory modalities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".