We introduce a class of artificial stimuli that lack preexperimental associations or encoding strategies. In a set of recognition memory experiments using these stimuli, we manipulate the similarity between studied items and between targets and foils, thus investigating the effects of pure perceptual similarity. We also assign values to studied items in order to induce encoding strategies that might emphasize encoding distinctive or overlapping features. Applying a stochastic signal detection model to these data, we find that blocked presentation and increased category size lead to poorer encoding of individual items, indicating that participants fail to encode distinctive features when list homogeneity is increased. Further, items assigned a negative value are encoded more poorly, a sign that participants may attempt to find overlapping features among negative items.