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Repetition of linguistic structure plays a role in both language comprehension and production. Previously encountered structures are processed faster, and speakers tend to reuse them in new utterances—a phenomenon known as structural priming. According to the prevailing interpretation of structural priming, linguistic input activates an underlying mental representation based on constituents, a syntactic unit derived from rule-based grammars (e.g., [[he]NP [hears [a sound]NP]VP]S). Here we ask whether structural priming can occur for non-constituent parts-of-speech fragments, such as pronoun verb determiner (e.g., he hears a). Across two preregistered phrasal decision experiments, we show that structural priming can occur at the level of three-word parts-of-speech sequences and in the absence of constituents. Using corpus analysis, we further show that structural priming of non-constituents also occurs in real-life dialogue. These results imply that constituent structure is not a necessary prerequisite for structural priming and provide a challenge to contemporary approaches to grammar.

CogSci 2023

Does he hears a prime I prefer the? Testing a novel chunk-based perspective on structural priming

## Welcome to EMNLP 2022!
I am delighted to welcome you to EMNLP 2022! I believe this conference has been complicated beyond any precedent. Over the past year, it’s been thrilling to see the organization team approach each new puzzle with creativity and enthusiasm. We hope that those participating in Abu Dhabi as well as those joining remotely will leave the conference feeling newly inspired by the program and newly connected to our ever-growing community. Following EMNLP 2021 and major NLP conferences since, EMNLP 2022 is “hybrid,” serving both virtual and in-person participants.

Our key innovations for EMNLP 2022 include:

* EMNLP 2022 is “hybrid” in a second sense, as well: we allowed both direct and rolling review paper submissions, building on the pilot experiment of EMNLP 2021, which considered a small number of ARR submissions. 
* Familiar from NAACL but new to EMNLP, we’ve added an industry track.
* During the conference, “portals” will link virtual poster sessions to in-person conference participants during poster sessions each day.
* The first ACL-family conference in the United Arab Emirates.

 *Message from Noah A. Smith, University of Washington and Allen Institute for AI, Seattle, Washington, USA* 
***EMNLP 2022 General Chair***
 
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EMNLP 2022

Welcome!
EMNLP 2022 will take place in Abu Dhabi from December 7th to December 11th, 2022. And it will be held in hybrid mode, both online and offline.

poster

The 45th Annual Meeting of the Cognitive Science Society will take place in Sydney, Australia as a modified hybrid conference. Presentations from the main-session room will be live-streamed every day for all events. This will include all invited talks and award sessions. Recordings of all CogSci 2023 sessions will be made available for on-demand viewing after the conference. 
The in-person component will be held at the International Convention Centre Sydney at Darling Harbour. The Conference will take place Wednesday July 26th – Saturday July 29th, 2023 (Wednesday, July 26th is the Workshops Day).

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 [**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2023/07/COgSci-PAAG-V2.pdf)
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#### **CogSci 2023 Program Book**
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The 45th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

The lesser known G(rammatical)-Maze task (Forster, Guerrera, & Elliot, 2009) is arguably a better choice than self-paced reading (Mitchell, 2004) for detecting difficulty from word to word in online sentence processing over crowdsourcing platforms. In G-Maze, a participant must choose between each successive word in a sentence and a distractor word that does not make sense based on the preceding context. If a participant chooses the distractor as opposed to the actual word, then the trial ends and they may not complete the sentence. Thus, G-Maze automatically filters out data from inattentive participants, and more effectively localizes differences in processing difficulty. Still, the effort required to pick contextually inappropriate distractors for hundreds of words might cause an experimenter to hesitate before picking this method. To save experimenters this time and effort, Boyce, Futrell, and Levy (2020) developed A(uto)-Maze, a tool that automatically generates distractors using a computational language model. We now introduce the next generation of A-Maze: T(ransformer)-Maze. Transformer models are the current state of the art in natural language processing, and thousands, pretrained in a variety of languages, are freely available on the internet, specifically through Huggingface’s Transformers package (Wolf et al., 2020). In our validation experiment, T-Maze proves itself to be as effective as G-Maze with handmade materials, run in a lab. This tool thus allows psycholinguists to easily gather high-quality online sentence processing data in many different languages.

Transformer-Maze: An Accessible Incremental Processing Measurement Tool

Logical connective words in natural languages often have multiple interpretations. A disjunction can be exclusive (XOR) or inclusive (IOR), and a negative conjunction can be interpreted as alternative denial (NAND) or joint denial (NOR). Previous research has suggested that there is substantial crosslinguistic variation in the interpretation of such logical constructions. That languages fall into two groups with different default interpretations. The first group interprets a negative conjunction as alternative denial (NAND) and a negative disjunction as joint denial (NOR). The second group has the opposite default interpretations. Using an online card selection task, we tested speakers of English, Hungarian, Spanish, and Mandarin on a wide variety of logical constructions. We found that the speakers of these languages did not show considerable variation in their interpretations of the logical constructions tested. The results suggest that the interpretation of logical constructions may be more consistent crosslinguistically than previously hypothesized.

Crosslinguistic Consistency in the Interpretation of Logical Connectives: The case of English, Hungarian, Spanish, and Mandarin Chinese

Visual attention can influence how language is processed. For instance, previous research showed that visual cueing of a referent affects the choice of a particular grammatical structure. The present study extended this research to language comprehension and investigated whether visually cueing either the subject or the object of an event affects the interpretation of a textual event description in Bulgarian with either a subject-initial or object-initial word order. The presence of the visual cue decreased self-paced reading reaction times and altered the accuracy in response to a comprehension question. Differences were found depending on the gender of the referent, highlighting the interaction of the visual cue and other linguistic information such as case marking. This study demonstrates that visually induced "context" can affect the linguistic salience of a referent in discourse and illustrates the interaction of domain-general cognitive mechanisms in language processing.

Visual cueing affects the processing of grammatical structure: A self-paced reading study on non-canonical word order in Bulgarian

Is there a cognitive bias against absolute synonymy? The current work explored this question via a miniature mini-artificial language experiment featuring iterated learning, which can amplify weak cognitive biases, as languages are sifted through multiple adult learners. Participants were taught two novel synonymous verbs in positive or negative sentences. Afterwards, they had to generalize the words to new positive or
negative sentences. These sentences then served as the input sentences for the next participant in the diffusion chain and so on. Despite inconsistent input with regard to positive or negative meaning, participants differentiated the verbs. More than half of participants strongly differentiated them, specializing at least one term. However, transmission did not increase differentiation overall, suggesting that a bias against synonymy may encourage a minimally distinctive difference, not necessarily a systematic one, between synonyms.

A Weak Bias Against Strong Synonymy?

Consider the following two (hypothetical) generic causal claims: “Attending an all-girls school improves girls’ math scores” and “attending an affluent all-girls school improves girls’ math scores.” These claims not only differ in what they suggest about how test scores are distributed across different types of schools (i.e., “the data”), but also have the potential to communicate something about the speakers’ values: namely, the prominence they accord to affluence in representing and making decisions about the social world. Here, we examine the relationship between the level of granularity with which a cause is described in a generic causal claim (e.g., all-girls school vs. affluent all-girls school) and the value of the information contained in the causal model that generates that claim. We argue that listeners who know any two of the following can make reliable inferences about the third: 1) the level of granularity at which a speaker makes a generic causal claim, 2) the speaker’s decision-theoretic values, and 3) the data available to the speaker. We present results of three experiments in the domain of social categories (N=853) that provide evidence in keeping with these predictions.

Tell Me Your (Cognitive) Budget, and I’ll Tell You What You Value: Evidential Relationships Between Values, Data, and Generic Causal Claims about the Social World

Positive emotional responses triggered by pleasant experiences can aid memorization ability in humans. However, little is known about the effect of aesthetically pleasing experiences on linguistic memory. To experimentally investigate whether aesthetic appeal promotes word memorability, study participants rated a set of artificial words on their aesthetic appeal and were asked to actively memorize them. In line with the predictions, higher-rated words were significantly likelier to be recollected and, interestingly, tended to contain similar patterns of phonemes. This suggests that phonemes contain an inherent aesthetic value and that linguistic memorization is aided by the presence of such aesthetically appealing sound patterns. This encourages further exploration of the effect of aesthetic perception on linguistic processing and allows for more objective approaches to assessing languages’ general appeal. Additionally, the results might have implications for the marketing industry where they allow for more efficient marketing strategies directly affecting their audience’s memory.

The effect of aesthetic appeal on words' memorability

The present research explored the development of prediction systems in 24- and 30-month-old toddlers in a visual world paradigm. Participants heard a sentence including correction (“no”) or conjunction (“and”) while seeing an array of pictures with an associatively related noun (“cat”) and the erroneous noun (“dog”). The young group showed an early prediction of the associative picture in both types of sentences, while the older group showed an early prediction of the coordination condition, but a later prediction in the correction sentences. Our results suggest that older toddlers deployed different predictive systems, while the younger group used the same system.

Linguistic Anticipation in Children’s Correction Sentences

Lexical diversity, the proportion of unique lemmas in a text, is known to vary across first language and second language production. It has been used by researchers as a proxy for language proficiency, particularly for classroom language learners. Lexical diversity has been found to vary by language background, potentially at least partly due to cross-linguistic influence. We investigated whether or how lexical diversity differs across groups with varied language backgrounds, namely monolinguals, bilinguals, adult language learners, and post-attrition speakers. We expected that these groups would show differing mean lexical diversity scores due to their different backgrounds with varying combinations of languages and levels of proficiency. Data from 114 participants were stratified and showed substantial between-group overlap in their lexical diversity scores. However, some significant by-group differences in lexical diversity were found. We discuss the implications of these results.

Lexical diversity across monolingual and multilingual populations

Speech pauses between conversational turns are crucial for assessing conversation partners’ cognitive states, such as their willingness to grant requests: Overall, speakers making longer pauses are regarded as less willing to comply with requests. We experimentally tested if the interpretation of pause length was mediated by the accent of interactants, in particular native versus non-native accents. In line with our prediction, in a rating task, participants judged non-native speakers to be equally willing to grant requests, irrespective of their inter-turn pause durations, whereas native speakers making long pauses were regarded as less willing than those making short pauses. This indicates that listeners interpret long pauses by non-native speakers as the result of prolonged cognitive processing needed for planning an answer in a non-native language rather than of a lack of willingness. This may have important implications for intercultural communication settings where topics are negotiated between native and non-native speakers.

Speech pause length predicts the attribution of willingness to help in native and non-native speakers

The principle of dependency length minimization, which seeks to keep syntactically related words close in a sentence, is thought to universally shape the structure of human languages for effective communication. However, the extent to which dependency length minimization is applied in human language systems is not yet fully understood. Preverbally, the placement of long-before-short constituents and postverbally, short-before-long constituents are known to minimize overall dependency length of a sentence. In this study, we test the hypothesis that placing only the shortest preverbal constituent next to the main-verb explains word order preferences in Hindi (a SOV language) as opposed to the global minimization of dependency length. We characterize this approach as a least-effort strategy because it is a cost-effective way to shorten all dependencies between the verb and its preverbal dependencies. As such, this approach is consistent with the bounded-rationality perspective according to which decision making is governed by `fast but frugal’ heuristics rather than by a search for optimal solutions. Consistent with this idea, our results indicate that actual corpus sentences in the Hindi-Urdu Treebank corpus are better explained by the least effort strategy than by global minimization of dependency lengths. Additionally, for the task of distinguishing corpus sentences from counterfactual variants, we find that the dependency length and constituent length of the constituent closest to the main verb is a much better predictor of whether a sentence appeared in the corpus than total dependency length. Overall, our work sheds light on the role of cognitive resource constraints in shaping natural languages.

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Transformer-Maze: An Accessible Incremental Processing Measurement Tool

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