The development of calendrical skills

Calendrical calculation is the unusual ability to name days of the week for dates in the past and sometimes the future. Previous investigations of this skill have concerned savants, people with pervasive developmental disorders or general intellectual impairment. This research has yielded a hypothesis about how calendrical skills develop but no direct evidence. This study attempts to learn about the development of savant skills by investigating the development of calendrical skills in two boys (aged 5 and 6) along with more general cognitive and social assessments. Consistent with the hypothesis, they initially demonstrated knowledge of regularities but limited range and accuracy in answering date questions and they were slower than many adult savants. At follow up, neither had improved their calendrical skills and they were less willing to answer date questions. Possibly this is because, unlike savants, they had developed interests more commonly shared by their peers and they now received praise for more conventional achievements

Structural Regularities in Text-based Entity Vector Spaces

Entity retrieval is the task of finding entities such as people or products in response to a query, based solely on the textual documents they are associated with. Recent semantic entity retrieval algorithms represent queries and experts in finite-dimensional vector spaces, where both are constructed from text sequences. We investigate entity vector spaces and the degree to which they capture structural regularities. Such vector spaces are constructed in an unsupervised manner without explicit information about structural aspects. For concreteness, we address these questions for a specific type of entity: experts in the context of expert finding. We discover how clusterings of experts correspond to committees in organizations, the ability of expert representations to encode the co-author graph, and the degree to which they encode academic rank. We compare latent, continuous representations created using methods based on distributional semantics (LSI), topic models (LDA) and neural networks (word2vec, doc2vec, SERT). Vector spaces created using neural methods, such as doc2vec and SERT, systematically perform better at clustering than LSI, LDA and word2vec. When it comes to encoding entity relations, SERT performs best.Comment: ICTIR2017. Proceedings of the 3rd ACM International Conference on the Theory of Information Retrieval. 201

Unifying cross-linguistic and within-language patterns of finiteness marking in MOSAIC

MOSAIC, a model that has already simulated cross-linguistic differences in the occurrence of the Optional Infinitive phenomenon, is applied to the simulation of the pattern of finiteness marking within Dutch. This within-language pattern, which includes verb placement, low rates of Optional Infinitives in Wh-questions and the correlation between finiteness marking and subject provision, has been taken as evidence for the view that children have correctly set the clause structure and inflectional parameters for their language. MOSAIC, which employs no built-in linguistic knowledge, clearly simulates the pattern of results as a function of its utterance-final bias, the same mechanism that is responsible for its successful simulation of the crosslinguistic data. These results suggest that both the crosslinguistic and within–language pattern of finiteness marking can be understood in terms of the interaction between a simple resource-limited learning mechanism and the distributional statistics of the input to which it is exposed. Thus, these phenomena do not provide any evidence for abstract or innate knowledge on the part of the child

The linguistics of gender

This chapter explores grammatical gender as a linguistic phenomenon. First, I define gender in terms of agreement, and look at the parts of speech that can take gender agreement. Because it relates to assumptions underlying much psycholinguistic gender research, I also examine the reasons why gender systems are thought to emerge, change, and disappear. Then, I describe the gender system of Dutch. The frequent confusion about the number of genders in Dutch will be resolved by looking at the history of the system, and the role of pronominal reference therein. In addition, I report on three lexical- statistical analyses of the distribution of genders in the language. After having dealt with Dutch, I look at whether the genders of Dutch and other languages are more or less randomly assigned, or whether there is some system to it. In contrast to what many people think, regularities do indeed exist. Native speakers could in principle exploit such regularities to compute rather than memorize gender, at least in part. Although this should be taken into account as a possibility, I will also argue that it is by no means a necessary implication

An analysis of word embedding spaces and regularities

Word embeddings are widely use in several applications due to their ability to capture semantic relationships between words as relations between vectors in high dimensional spaces. One of the main problems to obtain the information is to deal with the phenomena known as the Curse of Dimensionality, the fact that some intuitive results for well known distances are not valid in high dimensional contexts. In this thesis we explore the problem to distinguish between synonyms or antonyms pairs of words and non-related pairs of words attending just to the distance between the words of the pair. We considerer several norms and explore the problem in the two principal kinds of embeddings, GloVe and Word2Vec

Iterated learning and grounding: from holistic to compositional languages

This paper presents a new computational model for studying the origins and evolution of compositional languages grounded through the interaction between agents and their environment. The model is based on previous work on adaptive grounding of lexicons and the iterated learning model. Although the model is still in a developmental phase, the first results show that a compositional language can emerge in which the structure reflects regularities present in the population's environment