Limor Raviv

Publications

Displaying 1 - 8 of 8
  • Galke, L., & Raviv, L. (2025). Learning and communication pressures in neural networks: Lessons from emergent communication. Language Development Research, 5(1), 116-143. doi:10.34842/3vr5-5r49.

    Abstract

    Finding and facilitating commonalities between the linguistic behaviors of large language models and humans could lead to major breakthroughs in our understanding of the acquisition, processing, and evolution of language. However, most findings on human–LLM similarity can be attributed to training on human data. The field of emergent machine-to-machine communication provides an ideal testbed for discovering which pressures are neural agents naturally exposed to when learning to communicate in isolation, without any human language to start with. Here, we review three cases where mismatches between the emergent linguistic behavior of neural agents and humans were resolved thanks to introducing theoretically-motivated inductive biases. By contrasting humans, large language models, and emergent communication agents, we then identify key pressures at play for language learning and emergence: communicative success, production effort, learnability, and other psycho-/sociolinguistic factors. We discuss their implications and relevance to the field of language evolution and acquisition. By mapping out the necessary inductive biases that make agents' emergent languages more human-like, we not only shed light on the underlying principles of human cognition and communication, but also inform and improve the very use of these models as valuable scientific tools for studying language learning, processing, use, and representation more broadly.
  • Tsomokos, D. I., & Raviv, L. (2025). A bidirectional association between language development and prosocial behaviour in childhood: Evidence from a longitudinal birth cohort in the United Kingdom. Developmental Psychology, 61(2), 336-350. doi:10.1037/dev0001875.

    Abstract

    This study investigated a developmental cascade between prosocial and linguistic abilities in a large sample (N = 11,051) from the general youth population in the United Kingdom (50% female, 46% living in disadvantaged neighborhoods, 13% non-White). Cross-lagged panel models showed that verbal ability at age 3 predicted prosociality at age 7, which in turn predicted verbal ability at age 11. Latent growth models also showed that gains in prosociality between 3 and 5 years were associated with increased verbal ability between 5 and 11 years and vice versa. Theory of mind and social competence at age 5 mediated the association between early childhood prosociality and late childhood verbal ability. These results remained robust even after controlling for socioeconomic factors, maternal mental health, parenting microclimate in the home environment, and individual characteristics (sex, ethnicity, and special educational needs). The findings suggest that language skills could be boosted through mentalizing activities and prosocial behaviors.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2019). Larger communities create more systematic languages. Proceedings of the Royal Society B: Biological Sciences, 286(1907): 20191262. doi:10.1098/rspb.2019.1262.

    Abstract

    Understanding worldwide patterns of language diversity has long been a goal for evolutionary scientists, linguists and philosophers. Research over the past decade has suggested that linguistic diversity may result from differences in the social environments in which languages evolve. Specifically, recent work found that languages spoken in larger communities typically have more systematic grammatical structures. However, in the real world, community size is confounded with other social factors such as network structure and the number of second languages learners in the community, and it is often assumed that linguistic simplification is driven by these factors instead. Here, we show that in contrast to previous assumptions, community size has a unique and important influence on linguistic structure. We experimentally examine the live formation of new languages created in the laboratory by small and larger groups, and find that larger groups of interacting participants develop more systematic languages over time, and do so faster and more consistently than small groups. Small groups also vary more in their linguistic behaviours, suggesting that small communities are more vulnerable to drift. These results show that community size predicts patterns of language diversity, and suggest that an increase in community size might have contributed to language evolution.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2019). Compositional structure can emerge without generational transmission. Cognition, 182, 151-164. doi:10.1016/j.cognition.2018.09.010.

    Abstract

    Experimental work in the field of language evolution has shown that novel signal systems become more structured over time. In a recent paper, Kirby, Tamariz, Cornish, and Smith (2015) argued that compositional languages can emerge only when languages are transmitted across multiple generations. In the current paper, we show that compositional languages can emerge in a closed community within a single generation. We conducted a communication experiment in which we tested the emergence of linguistic structure in different micro-societies of four participants, who interacted in alternating dyads using an artificial language to refer to novel meanings. Importantly, the communication included two real-world aspects of language acquisition and use, which introduce compressibility pressures: (a) multiple interaction partners and (b) an expanding meaning space. Our results show that languages become significantly more structured over time, with participants converging on shared, stable, and compositional lexicons. These findings indicate that new learners are not necessary for the formation of linguistic structure within a community, and have implications for related fields such as developing sign languages and creoles.
  • Havron, N., Raviv, L., & Arnon, I. (2018). Literate and preliterate children show different learning patterns in an artificial language learning task. Journal of Cultural Cognitive Science, 2, 21-33. doi:10.1007/s41809-018-0015-9.

    Abstract

    Literacy affects many aspects of cognitive and linguistic processing. Among them, it increases the salience of words as units of linguistic processing. Here, we explored the impact of literacy acquisition on children’s learning of an artifical language. Recent accounts of L1–L2 differences relate adults’ greater difficulty with language learning to their smaller reliance on multiword units. In particular, multiword units are claimed to be beneficial for learning opaque grammatical relations like grammatical gender. Since literacy impacts the reliance on words as units of processing, we ask if and how acquiring literacy may change children’s language-learning results. We looked at children’s success in learning novel noun labels relative to their success in learning article-noun gender agreement, before and after learning to read. We found that preliterate first graders were better at learning agreement (larger units) than at learning nouns (smaller units), and that the difference between the two trial types significantly decreased after these children acquired literacy. In contrast, literate third graders were as good in both trial types. These findings suggest that literacy affects not only language processing, but also leads to important differences in language learning. They support the idea that some of children’s advantage in language learning comes from their previous knowledge and experience with language—and specifically, their lack of experience with written texts.
  • Raviv, L., & Arnon, I. (2018). Systematicity, but not compositionality: Examining the emergence of linguistic structure in children and adults using iterated learning. Cognition, 181, 160-173. doi:10.1016/j.cognition.2018.08.011.

    Abstract

    Recent work suggests that cultural transmission can lead to the emergence of linguistic structure as speakers’ weak individual biases become amplified through iterated learning. However, to date no published study has demonstrated a similar emergence of linguistic structure in children. The lack of evidence from child learners constitutes a problematic
    2
    gap in the literature: if such learning biases impact the emergence of linguistic structure, they should also be found in children, who are the primary learners in real-life language transmission. However, children may differ from adults in their biases given age-related differences in general cognitive skills. Moreover, adults’ performance on iterated learning tasks may reflect existing (and explicit) linguistic biases, partially undermining the generality of the results. Examining children’s performance can also help evaluate contrasting predictions about their role in emerging languages: do children play a larger or smaller role than adults in the creation of structure? Here, we report a series of four iterated artificial language learning studies (based on Kirby, Cornish & Smith, 2008) with both children and adults, using a novel child-friendly paradigm. Our results show that linguistic structure does not emerge more readily in children compared to adults, and that adults are overall better in both language learning and in creating linguistic structure. When languages could become underspecified (by allowing homonyms), children and adults were similar in developing consistent mappings between meanings and signals in the form of structured ambiguities. However, when homonimity was not allowed, only adults created compositional structure. This study is a first step in using iterated language learning paradigms to explore child-adult differences. It provides the first demonstration that cultural transmission has a different effect on the languages produced by children and adults: While children were able to develop systematicity, their languages did not show compositionality. We focus on the relation between learning and structure creation as a possible explanation for our findings and discuss implications for children’s role in the emergence of linguistic structure.

    Additional information

    results A results B results D stimuli
  • Raviv, L., & Arnon, I. (2018). The developmental trajectory of children’s auditory and visual statistical learning abilities: Modality-based differences in the effect of age. Developmental Science, 21(4): e12593. doi:10.1111/desc.12593.

    Abstract

    Infants, children and adults are capable of extracting recurring patterns from their environment through statistical learning (SL), an implicit learning mechanism that is considered to have an important role in language acquisition. Research over the past 20 years has shown that SL is present from very early infancy and found in a variety of tasks and across modalities (e.g., auditory, visual), raising questions on the domain generality of SL. However, while SL is well established for infants and adults, only little is known about its developmental trajectory during childhood, leaving two important questions unanswered: (1) Is SL an early-maturing capacity that is fully developed in infancy, or does it improve with age like other cognitive capacities (e.g., memory)? and (2) Will SL have similar developmental trajectories across modalities? Only few studies have looked at SL across development, with conflicting results: some find age-related improvements while others do not. Importantly, no study to date has examined auditory SL across childhood, nor compared it to visual SL to see if there are modality-based differences in the developmental trajectory of SL abilities. We addressed these issues by conducting a large-scale study of children's performance on matching auditory and visual SL tasks across a wide age range (5–12y). Results show modality-based differences in the development of SL abilities: while children's learning in the visual domain improved with age, learning in the auditory domain did not change in the tested age range. We examine these findings in light of previous studies and discuss their implications for modality-based differences in SL and for the role of auditory SL in language acquisition. A video abstract of this article can be viewed at: https://www.youtube.com/watch?v=3kg35hoF0pw.

    Additional information

    Video abstract of the article
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2018). The role of community size in the emergence of linguistic structure. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 402-404). Toruń, Poland: NCU Press. doi:10.12775/3991-1.096.

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