Goal-directed attention in late visual processing: On the scope and flexibility of feature-based attention
Bibliographic record
Abstract
Feature-based attention (FBA) has known effects on visual perception; however, its effects on later processing (i.e., visual working memory; VWM) are not well understood. Across three experiments I used a partial-report task to assess effects of FBA on the probability that items were encoded into VWM, and the precision of their representations. To investigate the flexibility of feature-based control I manipulated the likelihood that the feature-based goal would be relevant. Experiments 1 and 2 defined the relevant feature prior to encoding, and, to isolate later functioning, Experiment 3 defined the relevant feature per trial following encoding. Experiments 1 and 2 revealed that FBA affects both VWM probability and resolution, and these effects operate independently and flexibly. Experiment 3 revealed a later, less flexible mechanism for FBA. FBA has multiple effects on VWM that are separately influenced by the value of the goal, and the timing of when it is implemented.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 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".