United States

CogSci 2025

Synchronized development of possibility reasoning and theory-of-mind: Evidence from a cross-cultural study

developmental analysis

cognitive development

quantitative behavior

cross-cultural analysis

social cognition

theory of mind

culture

psychology

reasoning

### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

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#### About

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

#### Our History 

* **Society Creation**<br>
The Society was incorporated as a 501(c)(3) non-profit professional organization in Massachusetts in 1979. The organizing committee included Roger Schank, Allan Collins, Donald Norman, and a number of other scholars from psychology, linguistics, computer science, and philosophy. 
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* **Conference Creation**<br>
The first conference on cognitive science was held at La Jolla, California in August, 1979, and has occurred annually since then. The proceedings of each conference are published, and those from most years are available through Lawrence Erlbaum Associates, Inc. The annual proceedings of the Cognitive Science Conference represent a major source of information on new work and new ideas in the scientific study of thinking. In 1990, the Society, with help from an anonymous donor, established the David Marr Prize for the best student paper at each annual meeting.
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* **Journal Creation**<br>
The Journal, Cognitive Science, began publication in 1976, and is now published by Wiley-Blackwell. The Executive Editor is currently Richard P. Cooper of Birkbeck, University of London, and there are 18 Associate Editors and a 30-member editorial board. It serves as the premier outlet for research reports that intersect two or more disciplines. Copyrights for articles published in the journal are held by the Society. The Governing Board of the Cognitive Science Society voted in late 2006 to found a new journal, Topics in Cognitive Science (topiCS). The Editor in Chief is Wayne Gray, Cognitive Science Department, Rensselaer Polytechnic Institute. The journal seeks to fill a niche not occupied by Cognitive Science Journal or other cognitive science journals. Membership in the Society includes a subscription to Cognitive Science and TopiCS. Copyrights for articles published in the journal are held by the Society.
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#### Code of Conduct

By attending the CogSci 2025 Conference, you are required to adhere to the society’s **[Code of Conduct](https://drive.google.com/file/d/1ChPuihLy6jE_BWqfO7J2KKgX35JW2zsM/view?usp=sharing)**.
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The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

poster

Parents' beliefs about children's abilities shape their parenting practices. But how accurate are parents at estimating what children are truly capable of? Here, we test the hypothesis that U.S. parents underestimate young children's abilities to complete challenging, multi-step tasks, and in turn, intervene beyond children's developmental needs (a behavior known as "overparenting"). In Studies 1A and 1B, parents (N = 130) of preschool-aged children underestimated their children's abilities, especially on practical (vs. academic) and novel (vs. familiar) multi-step tasks. In Studies 2A and 2B, we found that parents' (N = 109) underestimation has potential negative consequences: Parents who believed their child was less capable were more likely to take over tasks and provided less encouragement for independent actions. These findings suggest that parents underestimate young children's abilities, which may hinder the development of children's learning and autonomy.

Parents underestimate young children's abilities which may undermine their parenting practices

Relying on information from other people (social testimony) is essential for efficiently learning and reasoning about the world. However, determining who to trust is often challenging. In this paper, we argue that trust in social agents (i.e., those providing testimony) can be evaluated by assessing how optimally they have acquired their knowledge. Building on theories that describe knowledge acquisition as a stochastic search through a space of hypotheses, we present a framework which yields predictions about which agents will provide better testimony (because they are more likely to have uncovered higher-probability hypotheses) in different contexts. This approach allows us to jointly predict how the quality of testimony is affected by 1) features of the agents themselves, like their expertise; 2) consensus among multiple agents; and 3) features of the topic and hypothesis space, like its knowability. We present initial simulations demonstrating how even a basic implementation of our framework yields insight into which types of agents and  topics are more likely to result in accurate testimony (and why). We conclude by discussing how this preliminary research might be extended to address more complicated social reasoning scenarios.

Stochastic search algorithms can tell us who to trust (and why)

Mind wandering during film viewing can impede comprehension and learning, and prior studies have reported conflicting results regarding its occurrence at event boundaries in narrative versus educational films. This study examines whether scene discontinuity – changes in time, place, character, and action – affects mind wandering differently across film genres. Replicating previous findings, we found that in the narrative film, less mind wandering occurred at event boundaries compared to other parts of the film. Conversely, in the educational film, more mind wandering was reported at event boundaries. Our analysis revealed that the narrative film exhibited higher scene discontinuity at event boundaries than the educational film. Importantly, across both film types, greater scene discontinuity at event boundaries was associated with decreased mind wandering. The differing levels of scene discontinuity between narrative and educational films may explain the contrasting patterns of mind wandering observed, highlighting the influence of film structure on cognitive engagement.

The influence of scene discontinuity on the relation between mind wandering and event boundaries

Distributional semantic models (DSMs) are computational models that learn semantic relationships through word co-occurrence patterns, broadly aligning with human statistical learning mechanisms. Prior research has shown that DSMs capture not only general semantic structure but also human social biases. For example, Caliskan et al. (2017) demonstrated that pre-trained word embeddings encode associations that mirror implicit stereotypes measured by the Implicit Association Test (IAT). To better understands how DSMs acquire these biases, we examined the roles of two distinct sources of distributional information: first-order (direct co-occurrence) and second-order (indirect co-occurrence)  statistics. Our analysis revealed that nearly all biases tested could be accounted for by first-order statistics alone, while about half were significant in second-order statistics. Every bias was present in at least one of these co-occurrence types, with nuanced variation in how different topics exhibited bias across first- and second-order associations. These findings suggest that implicit biases in DSMs can be attributed to simple co-occurrence patterns, predominantly direct associations. Moreover, they support theories positing that implicit biases reflect statistical regularities in the environment rather than personal attitudes. This work highlights how these biases are embedded in natural language and how a cognitive system capable of statistical learning could acquire implicit biases through the same mechanisms that shape human semantic memory.

Decomposing Implicit Bias in Distributional Semantic Models: The Roles of First- and Second-Order Co-Occurrence

Heritage bilinguals—who learned their L1 in their childhood home and L2 at school—vary greatly in their language and literacy skills. Although much is known about heritage bilingual children’s language and literacy development, less understood are psycholinguistic processes underlying literacy skills in heritage bilingual adults, which we examined here. Spanish(L1)-English(L2) heritage bilingual adults completed psycholinguistic and reading tasks in English and Spanish. Although participants’ English and Spanish verbal fluency did not significantly differ (t=1.750, p=.118), they read sight words more efficiently in English than Spanish (t=5.371, p<.001), suggesting asymmetries in language versus literacy skills. However, participants had better recollection for and familiarity with passages read in Spanish than English (ts>2.014, ps<.04), despite lower d’ scores in Spanish than English reflecting greater uncertainty (t=1.681, p=.066). These findings suggest that memory is richer for passages read in Spanish than English, despite reading being more efficient in English than Spanish.

Heritage Language vs. Dominant Language: When Bilinguals Excel in Unexpected Ways

The speech young children hear is highly variable. For example, reduced pronunciations, where some sounds in the canonical pronunciation are naturally dropped or altered, are common even in speech to children. The present study employed a new story-guided looking method (a variation on language-guided looking) to create felicitous conditions for testing young children’s recognition of reduced pronunciations of familiar words. Experiment 1 (18-24 months, n=32) found that toddlers succeeded at recognizing clear pronunciations, but failed to recognize reduced pronunciations, even in repetition trials when target words were preceded by a clear mention of the same word in the previous sentence. In Experiment 2, 3-year-olds (35-39 months, n=17 out of 44 pre-registered, ongoing) succeeded at recognizing reduced pronunciations, and benefited from preceding repetition. Overall, these results demonstrate a powerful new method for studying children’s language comprehension under more naturalistic conditions, and highlight an important psycholinguistic development over the 2–3 year span.

Development in the comprehension of phonetically reduced spoken words

This paper explores how personalized recommendation algorithms may inadvertently create echo-chambers, leading to the emergence of political issue polarization in online networks. Using an Agent-Based Modelling (ABM) approach, we conducted two studies, simulating users in three distinct algorithm designs. In Study 1, we found that personalized 
recommendation algorithms had a small but significant effect on increasing polarization, even among rational Bayesians. In Study 2, we introduced users with novelty-seeking preferences. Contrary to previous literature, our findings suggested interventions targeting personalization bubbles are ineffective, as introducing novelty-seeking preferences had no significant effect on reducing polarization levels. Together, our findings highlight the importance of algorithmic influence in creating online polarization, offer implications for social media network design, and urge caution regarding existing interventions aimed at minimizing polarization.

Recommender Systems Issue Polarization in Social Networks

How do vision-language (VL) transformer models ground verb phrases and do they integrate contextual and world knowledge in this process? We introduce the CV-Probes dataset, containing image-caption pairs involving verb phrases that require both social knowledge and visual context to interpret (e.g., `beg'), as well as pairs involving verb phrases that can be grounded based on information directly available in the image (e.g., ``sit"). We show that VL models struggle to ground VPs that are strongly context-dependent. Further analysis using explainable AI techniques shows that such models may not pay sufficient attention to the verb token in the captions. Our results suggest a need for improved methodologies in VL model training and evaluation. The code and dataset will be available https://github.com/ivana-13/CV-Probes.

CV-Probes: Studying the interplay of lexical and world knowledge in visually grounded verb understanding

Multi-Agent Systems (MAS) are increasingly used to simulate social interactions, but most of the frameworks miss the underlying cognitive complexity of human behavior. In this paper, we introduce Trans-ACT (Transactional Analysis Cognitive Toolkit), an approach embedding Transactional Analysis (TA) principles into MAS to generate agents with realistic psychological dynamics. Trans-ACT integrates the Parent, Adult, and Child ego states into an agent’s cognitive architecture. Each ego state retrieves context-specific memories and uses them to shape response to new situations. The final answer is chosen according to the underlying life script of the agent. Our experimental simulation, which reproduces the Stupid game scenario, demonstrates that agents grounded in cognitive and TA principles produce deeper and context-aware interactions. Looking ahead, our research opens a new way for a variety of applications, including conflict resolution, educational support, and advanced social psychology studies.

Games Agents Play: Towards Transactional Analysis in LLM-based Multi-Agent Systems

Many causal relations can be represented by continuous functions that map inputs to outputs. Can young children learn continuous causal functions and generalize them from observed data to new scenarios? We found that 4- and 5-year-olds can represent continuous functions with different abstract forms. After observing a few input-output pairs, children can accurately infer positive linear and step functions by predicting the outputs of novel input values. They also have emerging knowledge of negative linear and triangular functions. While children do not yet make consistently accurate predictions for these functions, they can distinguish these functions from the positive linear function and show inferential patterns that are consistent with the respective functions. Like adults and older children, preschoolers show an inductive bias towards positive linear functions. Their understanding of negative linear functions--which strongly requires inhibiting this inductive bias--improves with age.

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Parents underestimate young children's abilities which may undermine their parenting practices

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