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  1. Abstract Contrary to common intuition, a group of people recalling information together remembers less than the same number of individuals recalling alone (i.e., the collaborative inhibition effect). To understand this effect in a free recall task, we build a computational model of collaborative recall in groups, extended from the Context Maintenance and Retrieval (CMR) model, which captures how individuals recall information alone. We propose that in collaborative recall, one not only uses their previous recall as an internal retrieval cue, but one also listens to someone else’s recall and uses it as an external retrieval cue. Attending to this cue updates the listener’s context to be more similar to the context of someone else’s recall. Over an existing dataset of individual and collaborative recall in small and large groups, we show that our model successfully captures the difference in memory performance between individual recall and collaborative recall across different group sizes from 2 to 16, as well as additional recall patterns such as recency effects and semantic clustering effects. Our model further shows that collaborating individuals reach similar areas in the context space, whereby their contexts converge more than the contexts of individuals recalling alone. This convergence constrains their ability to search memories effectively and is negatively associated with recall performance. We discuss the contributions of our modeling results in relation to previous accounts of the collaborative inhibition effect. 
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  2. Contrary to common intuition, groups of people recalling information together remember less than the same number of individuals recalling alone (i.e., the collaborative inhibition effect). To understand this effect in a free recall task, we build a computational model of collaborative recall in groups, extended from the Context Maintenance and Retrieval (CMR) model which captures how individuals recall information alone (Polyn, Norman, & Kahana, 2009). We propose that in collaborative recall, one not only uses their previous recall as an internal retrieval cue, but also listens to someone else’s recall and uses it as an external retrieval cue. Attending to this cue updates the listener’s context to be more similar to the context of someone else’s recall. Over an existing dataset of individual and collaborative recall in small and large groups (Gates, Suchow, & Griffiths, 2022), we show that our model successfully captures the difference in memory performance between individual recall and collaborative recall across different group sizes from 2 to 16, as well as additional recall patterns such as recency effects and semantic clustering effects. Our model further shows that the contexts of collaborating individuals converge more than the contexts of individuals who recall alone. We discuss the contributions of our modeling results in relation to previous accounts of the collaborative inhibition effect. 
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  3. We often use cues from our environment when we get stuck searching our memories, but prior research has failed to show benefits of cuing with other, randomly selected list items during memory search. What accounts for this discrepancy? We proposed that cues’ content critically determines their effectiveness and sought to select the right cues by building a computational model of how cues affect memory search. Participants ( N = 195 young adults from the United States) recalled significantly more items when receiving our model’s best (vs. worst) cue. Our model provides an account of why some cues better aid recall: Effective cues activate contexts most similar to the remaining items’ contexts, facilitating recall in an unsearched area of memory. We discuss our contributions in relation to prominent theories about the effect of external cues. 
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