United States

In bilinguals, certain concepts across languages come to be represented similarly—a semantic convergence effect that reflects interactivity between languages. The causal factors that affect semantic convergence are not fully understood; this gap may be due to limitations of the correlative methods used in extant work, which assesses the representations of real-world bilinguals. Here, we utilize an artificial language learning paradigm—inspired by the study of category learning—to elucidate causal influences on semantic convergence. We contrast simulated simultaneous bilingual learners with simulated sequential bilingual learners before assessing the representations of both. Bilingual groups are additionally compared to simulated monolingual controls from each language. We report on the pattern of semantic convergence and conclude with implications for theories of bilingual representation.

CogSci 2021

Now or Later: Representational Convergence in Simulated Simultaneous and Sequential Bilingual Learning Contexts

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

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IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.

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### Looking for Cogsci 2023? Please [click here](https://underline.io/events/405/reception) to switch to 2023 edition.


**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year! 

**Your Program Chairs,**
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**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

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To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).

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.

Anaphora, a ubiquitous feature of natural language, poses a particular challenge to young children as they first learn language due to its referential ambiguity. In spite of this, parents and caregivers use anaphora frequently in child-directed speech, potentially presenting a risk to effective communication if children do not yet have the linguistic capabilities of resolving anaphora successfully. Through an eye-tracking study in a naturalistic free-play context, we examine the strategies that parents employ to calibrate their use of anaphora to their child's linguistic development level. We show that, in this way, parents are able to intuitively scaffold the complexity of their speech such that greater referential ambiguity does not hurt overall communication success.

Parents Adaptively Use Anaphora During Parent-child Social Interaction

We investigated racial bias in emotion inference by having participants describe the emotion of the featured person in the image, including Asian, Black, and White. We collected 4,197 sentences (63,900 tokens) and used the data to train Word2Vec, a neural network-based word embedding model. We calculated the cosine distance between emotion words and words indicating the target for each racial group in order to measure the strength of association. Although all images portrayed neutral emotions, the results show that negative emotion words were close to Asian and Black, whereas neutral words were close to White. This result indicates that stereotypes contribute to the racial bias in Artificial Intelligence as crowdsourcing workers can generate annotations depending on the featured person's race. Based on the present study, we suggest employing various de-biasing methods such as data augmentation or removing bias components in word embeddings before using Artificial Intelligence in the real world.

Racial Bias in Emotion Inference: An Experimental Study Using a Word Embedding Method

Temporal gestures reveal our metaphorical thinking of time. Less is known about how speakers of different languages encode temporal gestures. We asked 19 adults to explain the meanings of 12 spatial metaphors of time in Turkish sentences. We coded gestures according to the coding scheme of Cooperrider and Nuñez (2009). Individuals produced 237 temporal gestures. There were 162 placing (68.35%), 10 pointing (4.22%), 13 duration-marking (5.49%), 12 bridging (5.06%), 40 animating (16.88%) gestures. We also identified 61 temporal gestures that did not fall into any category in their classification. These gestures depicted the change of the time of an event caused by humans (e.g., to postpone a meeting) with an open hand moving the events along an axis. We termed these as “moving” gestures and suggest that speakers of different languages may vary in their representations of temporal gestures.

Temporal Gestures in Turkish Metaphor Explanations

We explore how morphological cue occurrence and frequency-based heuristics interplay during sentence comprehension in Korean, a lesser-studied language in this respect. Two self-paced reading experiments with a suffixal passive construction (verb-final vs. verb-initial) and a morphological causative construction (verb-initial in comparison to the same word-order pattern in the suffixal passive) revealed that the heuristics (canonicity of word order; typicality of form-function parings involving case-marking) affected processing behaviours more strongly than the expected advantage of an early-arriving morphological cue in comprehension. Our findings support the heuristic-before-algorithm processing architecture, which is driven by the general property of human cognition that continuously seeks to reduce the burden of work at hand at the earliest opportunities. This appeals to the online cognitive equilibrium hypothesis that argues for the processor’s propensity to enter and remain in the state of cognitive equilibrium as early and long as possible during processing.

Keep Calm and Move On: Interplay between Morphological Cue Occurrence and Frequency-based Heuristics for Sentence Comprehension in Korean

During language comprehension, words are easier to process when predictable based on local sentence context. It is unclear how information available from the global discourse interacts with this local predictive processing. To test this, we conducted an online self-paced reading study (n=100), manipulating the predictability of a critical word in a target sentence while varying the coherency of the target sentence with a preamble context that preceded it. We found that people processed the critical word faster when it was highly predictable from local context, replicating a common finding. We also found people were slower to process the critical word when the target sentence was presented in an incoherent context. However, no interaction was observed. Results indicate that subtler semantic changes, such as topic shifts, slow language processing but do not reduce the benefit of a highly predictable, local context.

Effects of global discourse coherence on local contextual predictions

Rational Speech Act theory (Frank & Goodman, 2012) has been successfully applied in numerous communicative settings, including studies using one-shot web-based language games. Several follow-up studies of the latter, however, suggest that listeners may not behave as pragmatically as originally suggested in those tasks. We investigate whether, in such reference games, listeners’ pragmatic reasoning about an informative speaker is improved by greater exposure to the task, and/or prior experience with being a speaker in this task. While we find limited evidence that increased exposure results in more pragmatic responses, listeners do show increased pragmatic reasoning after playing the role of the speaker. Moreover, we find that only in the Speaker-first condition, participant’s tendency to be an informative speaker predicts their degree of pragmatic behavior as a listener. These findings demonstrate that, in these settings, experience as a speaker enhances the ability of listeners to reason pragmatically, as modeled by RSA.

Speak before you listen: Pragmatic reasoning in multi-trial language games

We introduce the LARC-ID, a pilot corpus of eye-movements obtained from subjects reading texts from a range of genres. Materials were presented in multiple paragraphs on the screen to more closely match naturalistic reading environments. Readers were encouraged to read for comprehension and enjoyment, engaging in various kinds of comprehension questions, including an open-ended reflection at the end of each text. Subjects also participated in a battery of individual difference measures, including those known to predict reading behavior in controlled experimental contexts, e.g., Rapid Automatized Naming (RAN; Denckla & Rudel, 1976), the author recognition (ART; Stanovich & West, 1989), and reading span (RSpan; Daneman & Carpenter, 1980) tasks. In addition to describing the central properties of the text and relationships between tasks in the battery, we present a sample analysis exploring how intrinsic lexical characteristics (length, frequency, and morphological complexity) interact with selected individual difference measures. The analysis provides the very first glimpse into what we hope will become a useful resource for reading researchers and educators. The entire corpus is freely available for unrestricted use.

Los Angeles Reading Corpus of Individual Differences: Pilot distribution and analysis

The paper addresses both issues of first language (L1) attrition and second language (L2) acquisition in the context of two mutually intelligible languages from a psycholinguistic perspective. It summarises results of a study examining how native speakers of Slovak living long-term in Czechia process and produce Slovak and Czech cognates and noncognates. Two experimental sessions consisting of lexical decision task and picture naming task were conducted once with Slovak stimuli and once with Czech stimuli. The results showed that Slovak noncognates were processed and produced more slowly by Slovaks who use their L1 less, and their L2 more. Analogically, this subgroup processed and produced Czech noncognates relatively faster. Thus, the experiments give evidence of (a) L1 attrition (online processing difficulties), and (b) the shift towards L2 patterns depending on the amount of L1 and L2 use even in speakers of two very close and mutually intelligible languages.

Slovaks in Czechia: L1 Attrition and L2 Acquisition in Two Mutually Intelligible Languages

Listeners adapt to variability in language use by updating their expectations over variants, often in speaker-specific ways. We propose that adaptation of this sort contributes to satiation, the phenomenon whereby the acceptability of unacceptable sentences increases after repeated exposure. We provide support for an adaptation account of satiation by showing that the satiation of purportedly unacceptable island-violating constructions demonstrates speaker-specificity, a key property of adaptation.

Syntactic satiation is driven by speaker-specific adaptation

This study investigated whether bilingual experience would influence young adults’ integration of multiple cues to infer a speaker’s intention. Using a cue-integration task coupled with eye-tracking, we examined the effects of balanced language usage on young bilingual adults’ ability to integrate multiple cues in determining a speaker’s referential intent. Behavioral and eye-tracking findings indicated that balanced bilinguals were better able than unbalanced bilinguals in identifying a target object in the three-cue condition (i.e., contextual, semantic and gaze cues were shown). However, there were no group differences in the two-cue condition (i.e., only contextual and semantic cues were shown). Our results suggest that the extent of bilingualism could modulate the sensitivity to and integration of multiple cues in the intention-inference process. We argue that balanced bilinguals’ greater exposure to complex communicative situations could enhance their ability in utilizing multiple cues to understand a speaker’s intention.

Now or Later: Representational Convergence in Simulated Simultaneous and Sequential Bilingual Learning Contexts

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Parents Adaptively Use Anaphora During Parent-child Social Interaction

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