United States

Prominent U.S. legal cases have turned on the resolution of linguistic ambiguities that arise from interactions between negation and coordination. Negative disjunction sentences (ND, “John didn’t buy cake or cookies”) are ambiguous between two readings: a neither-nor reading and a not-both reading. Negative conjunction (NC, “John didn’t buy cake and cookies”) is similarly ambiguous. Experimental findings on such scope ambiguities (Jasbi et al. 2023, Tobia et al. 2023) suggest that in general, listeners favor the neither-nor reading for ND but are less biased in their interpretations of NC. We present a corpus analysis with researcher annotations of several hundred tokens of these constructions in English treebank data. Initial results are consistent with previous conclusions based on controlled experimental data, suggesting that an attested tendency in linguistic comprehension is also reflected in naturalistic production. Our dataset can further be used to explore factors that modulate the disambiguation in context.

CogSci 2025

Scope Ambiguity Resolution of Negated Connectives in English Corpora

semantics of language

language comprehension

language production

linguistics

pragmatics

poster

### 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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The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Understanding speech demands integration of various kinds of information over time. Previous research has shown that listeners can use both semantic and acoustic cues to understand spoken words (Bushong, 2024) and that listeners can dynamically reweight different acoustic cues relative to each other (Kapatsinski, 2024); but it is unclear if listeners are able to readjust the relative contributions of semantic and acoustic cues depending on the current context (e.g. adverse listening conditions). The current study manipulates the acoustics of a target word, a semantic cue (sentential context), and the location of the semantic cue relative to the target word. Additionally, we manipulate the level of noise in the utterance and the location of that noise (full utterance vs. target word). Noise reduces listeners’ ability to use acoustic cues for spoken word recognition and as local noise increases, semantic context is up-weighted. However, as global noise increases, semantic context is also down-weighted.

Listener Trade-Offs between Acoustics and Semantics in Noisy Speech

Models of events represent the interactions of the entities involved. In the event “The chef chopped an onion," a chef and an onion are explicitly involved, and the event results in a chopped onion. However, it is also implied that an instrument, e.g., a knife, must interact with the chef and the onion. In this study, we investigate the extent to which people model different implicit instruments in event representations. We find that people's representations of events reliably include instruments that are implied to be involved even when they are not explicitly stated in the event description. These findings are consistent across different sentence constructions of events, suggesting that implicit instrument representation is robust in comprehension of events. We also show that implicit instrument representation persists despite lexical priming of other items, and that the representations provide evidence for the disambiguation of the Instrument semantic role from other semantic role categories.

Experimentally extracting implicit instruments

The word-frequency distributions infants hear during language learning are highly skewed (Zipfian). Previous work suggests that such skewed distributions facilitate speech segmentation, a crucial milestone in language acquisition. However, the experimental studies supporting this have only examined individuals aged 10 years or older, and it is not clear whether this effect arises from accumulated linguistic experience or is already present in the early stages of learning. To address this, we ran a word-segmentation study with 8-month-old infants (N=60) by exposing them to a continuous speech stream with a skewed or uniform frequency distribution of artificial words. At test, infants in the skewed condition exhibited a larger looking time difference between heard and unheard words than infants in the uniform condition. These findings suggest that Zipfian distributions can facilitate word segmentation during early linguistic development, and highlight the importance of the distributional characteristics of linguistic input in natural language learning

Zipfian distributions facilitate word segmentation in infants

This study aimed to explore the relationship between ESL learners' cognitive styles and personality types, focusing on how personality influences perceptual learning preferences and language learning strategies. Participants included 20 English majors and 58 Nursing majors in a Year 1 ESL course (62 females and 16 males). Data were collected using a structured questionnaire, including the Myers-Briggs Type Indicators (MBTI) test, and 40 items on learning styles and strategies. Results indicated that the most common personality types among English majors were INFP and ISFP, while Nursing majors frequently exhibited ISFJ and ENFP types. The least common types were INTJ and ENTP. Learning style preferences showed 37% favored reading/writing, 33% visual, 26% auditory, and 4% kinesthetic. Significant relationships were found between language learning strategies and introverted/extroverted personality types, though no significant gender differences were observed. The findings suggest that ESL instructors should consider these differences to enhance classroom dynamics and effectiveness.

The Impact of Personality Types and Cognitive Learning Styles on ESL Learners in Art and Science Programmes

Humans’ capacity for Theory of Mind (ToM) allows us to reason about and infer others’ mental states, including their emotions. While ToM has been extensively studied in interpersonal contexts, how people attribute mental states–particularly emotions–to collective entities (e.g., corporations) remains underexplored. The current work examines whether and how people ascribe emotions to collectives using the appraisal theory framework. Participants were randomly assigned to scenarios designed to elicit a specific emotional inference about either an individual (e.g., a lawyer) or a collective (e.g., a law firm). We then collected and compared emotion attributions and appraisal judgments of the situations across both conditions. Our results suggest that people attribute emotions to individuals and collectives in remarkably similar ways, with subtle differences in event appraisals. The results pave the way for a deeper understanding of collective ToM, with implications for studying moral judgments and decision-making in societal contexts.

Collective Emotions: Appraisal-based similarity in emotion attributions to individuals and groups

How do language models assign responsibility and reward, and is it similar to how humans do it? We instructed three state-of-the-art large language models to assign responsibility (Experiment 1) and reward (Experiment 2) to agents in a collaborative task. We then compared the language models’ responses to seven existing cognitive models of responsibility and reward allocation. We found that language models mostly evaluated agents based on force (how much they actually did), in line with classical production-style accounts of causation. By contrast, humans valued actual and counterfactual effort (how much agents tried or could have tried). These results indicate a potential barrier to effective human-machine collaboration.

Language models assign responsibility based on actual rather than counterfactual contributions

Pragmatic atypicality is widely considered to be a central characteristic of autism. This is often explained as a consequence of Theory of Mind deficits. However, this account is flawed and biased. In this paper, we revisit the Double Empathy Problem and provide an experience-first approach to autistic pragmatics. We start with proposing a mechanistic explanation of a link between experiential differences and intentionality understanding in linguistic contexts using the Interpretive Sensory Access theory. Then, we explain how theories of common ground in communication involve factors beyond intention recognition and even beyond cooperation, highlighting how the egocentric nature of communication is relevant to one’s attention and experiences. Taken together, we put forward an experience-based approach to understand autistic pragmatic atypicalities. This view is compatible with many other non-linguistic characteristics well-documented in autism, and prioritizes the experience of autistic people, instead of framing it as a communication disorder with a “mind-reading failure”.

An Experience-First Approach to Autistic Pragmatics 

People can adjust how fast they update task rules, depending on the volatility of their environment. We investigated whether this adaptivity is primarily driven by recently experienced volatility in task demands, or can also be shaped by learned, environment-specific associations with expected levels of volatility. To this end, we trained participants on a Wisconsin Card Sorting Task where different environments required different speeds of task rule updating. We demonstrate that, initially, participants updated strategies depending on the most recent experienced levels of volatility and feedback (Experiment 1). However, after extensive (four days) training (Experiment 2), participants also developed environment-specific associations. Our findings provide important insights in how people learn to regulate cognitive flexibility.

Learning task rule updating strategies requires extensive practice 

Word meanings are rarely transparent from their extralinguistic contexts. How children learn words from an input with “low-informative” (LI) events is of interest because even adults struggle to learn from LI events (Gleitman & Trueswell, 2020; Medina et al., 2011). This study revisited LI events’ contribution to learning by probing what can be gleaned from LI events even if they don’t yield exact meanings. Adults (N = 120) learned words (e.g., “modi”) that had English meanings (e.g., “apple”) from LI events. Participants then both guessed the word’s exact meaning and rated several candidate meanings. Although LI events failed to yield accurate mappings of meanings, they led to representations (derived via the ratings) that were semantically aligned with those of the true meanings. These results highlight the potential for LI events to get learning off the ground and the implications of viewing word learning as more than a mapping problem.

Beyond Word Meaning Mappings: The Role of Low-Informative Events in Conceptual Alignment

The current study investigates how pronominal ambiguity is resolved in real-time, focusing on the role of referent bias and task context. In two self-paced reading experiments, we tested whether ambiguity leads to processing benefits or costs modulated by the presence of a biased referent and the task manipulations. Experiment 1 showed that the ambiguity advantage emerges only when a biased referent is not selected, supporting reanalysis-based accounts such as the unrestricted race model (Van Gompel et al., 2000, 2001, 2005). Experiment 2, however, revealed a delayed ambiguity penalty, suggesting task-induced shifts in processing strategy that better fit a delayed interpretation account. These findings highlight that pronominal ambiguity resolution may involve two processing mechanisms shaped by the parser's evaluation space and the timing of selection.

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Listener Trade-Offs between Acoustics and Semantics in Noisy Speech

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Listener Trade-Offs between Acoustics and Semantics in Noisy Speech

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