Large number of weights in deep neural networks makes the models difficult to be deployed in low memory environments such as, mobile phones, IOT edge devices as well as “inferencing as a service” environments on cloud. Prior work has considered reduction in the size of the models, through compression techniques like pruning, quantization, Huffman encoding etc. However, efficient inferencing usi...

Density and distribution of Unfamiliar Lexical Items (ULIs) appear to influence learners’ Reading Comprehension Achievement (RCA). This study concerns the impact of these two variables on Iranian EFL learners’ RCA. For this, two groups of students timetabled for the experiments designed to assess learners’ RCA. To determine the participants’ levels of proficiency a Quick Proficiency Test was fi...

Density and distribution of Unfamiliar Lexical Items (ULIs) appear to influence learners’ Reading Comprehension Achievement (RCA). This study concerns the impact of these two variables on Iranian EFL learners’ RCA. For this, two groups of students timetabled for the experiments designed to assess learners’ RCA. To determine the participants’ levels of proficiency a Quick Proficiency Test was fi...

PURPOSE A hallmark of autistic spectrum disorder (ASD) is disruption in theory-of-mind development, including the understanding of false beliefs. Previous studies have typically assessed the development of first- and second-order false belief concepts in ASD, with tasks primarily emphasizing physical causality and logical inferencing. The present study investigated how preadolescents and adoles...

Explaining how the meaning of words relate to the meaning of the utterance in which they are used is of utmost importance. The most common approaches view the meaning of an utterance as a composition of the meanings of it parts, which of course include the words used to construct the utterance. This approach is successful for entailments. However, similar approaches to explain the presuppositio...

Broad-coverage ontologies which represent lexical semantic knowledge are being built for more and more natural languages. Such resources provide very useful information for word sense disambiguation, which is crucial for a variety of NLP tasks (e.g. semantic annotation of corpora, information retrieval, or semantic inferencing). Since the manual encoding of such ontologies is very labour-intens...

Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topic-oriented, informative multi-document summarization where the goal is to produce a single text as a compressed version of a set of documents with a minimum loss of relevant information. In this paper, we experiment with one empirical method and two unsupervised statistic...