While large language models (LLMs) continue to grow in scale and gain new zero-shot capabilities, their performance for languages beyond English increasingly lags behind. This gap is due to the "curse of multilinguality," where multilingual language models perform worse on individual languages than a monolingual model trained on that…

The essence of human intelligence lies in its ability to learn continuously, accumulating past knowledge to aid in future learning and problem-solving endeavors. In contrast, the current machine learning paradigm often operates in isolation, lacking the capacity for continual learning and adaptation. This deficiency becomes apparent in the face of…

The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…

Linguistic meaning is generated by the mind and can be expressed in multiple languages. One may assume that equivalent texts/utterances in two languages by means of translation generate equivalent meanings in their readers/hearers. This follows if we assume that meaning calculated from the linguistic input is solely objective in nature. However,…

Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…

The use of technology as a facilitator in learning environments has become increasingly prevalent with the global pandemic caused by COVID-19. As such, computer-supported collaborative learning (CSCL) gains a wider adoption in contrast to traditional learning methods. At the same time, the need for automated tools capable of assessing and…

Syntactic structures are unobserved theoretical constructs which are useful in explaining a wide range of linguistic and psychological phenomena. Language acquisition studies how such latent structures are acquired by human learners through many hypothesized learning mechanisms and apparatuses, which can be genetically endowed or of general…

Competence is defined as the knowledge of a mature speaker of a language, irrespective of questions about acquisition. It is questioned whether there can be a procedure for generating sentences as a model of this competence; it is concluded that there cannot be a precise, non-random model for competence. (CHK)

Presents a model for the a priori analysis of natural language queries which uses an algorithm to transform the query into a logical pattern that is used to determine the answerability of the query. The results of testing by a prototype system implemented in PROLOG are discussed. (20 references) (CLB)

Describes a model that displays structures necessary to map between the conceptual and external levels in database management systems, using an algorithm that maps the syntactic representations of tuples onto semantic representations. A technique for translating tuples into natural language sentences is introduced, and a system implemented in…

Proposes that topic representations should consist of excerpts from domain thesaurus, generated by spreading activation technique. Algorithm for generating excerpts is outlined and exemplified, and problem of assessing resemblance between two excerpts is discussed. Whether existing thesauri are adequate for this purpose is questioned, and ideas…

Presents a framework for studying the effects of the Maturation Hypothesis on the problem of language learning, parametrically conceived, and offers a method for finding all existing maturational solutions for any parametric hypothesis space and any learning algorithm that differs from Gibson and Wexler's Triggering Learning Algorithm. (27…

The learning machine described in this paper acquires concepts representable as conjunctive forms of the predicate calculus and behaviors representable as productions (antecedent-consequent pairs of such conjunctive forms): these concepts and behavior rules are inferred from sequentially presented pairs of examples by an algorithm that is probably…