Text Summarization is compressing the source text into a shorter version preserving its information content and overall meaning. It is very complicated for human beings to manually summarize large documents of text. Text summarization plays an important role in the area of natural language processing and text mining. Many approaches use statistics and machine learning techniques to extract sent...

Naturally-occurring instances of linguistic phenomena are important both for training and for evaluating automatic text processing. When available in large quantities, they also prove interesting material for linguistic studies. In this article, we present WiCoPaCo (Wikipedia Correction and Paraphrase Corpus), a new freely-available resource built by automatically mining Wikipedia’s revision hi...

these two girls' productions, particularly the various types of distortion of the naturalistic appearance of objects, are also employed by the most original and successful artists, for instance, Paul Klee and Picasso. She says we do not know whether these artists achieved this mode of expression through subjective experimentation, or by being influenced by seeing the art of mentally disturbed p...

We introduce a novel probabilistic Boolean logic (pbl) in which the probabilistic disjunction, conjunction and negation operators, provide the “output” expected of their deterministic counterparts, with a probability p. By design, this output can be incorrect with a probability (1− p). In order to distinguish our approach to injecting probabilities into Boolean logic from past approaches, we in...

Abstract Consistency of a model—that is, the invariance its behavior under meaning-preserving alternations in input—is highly desirable property natural language processing. In this paper we study question: Are Pretrained Language Models (PLMs) consistent with respect to factual knowledge? To end, create ParaRel

We address the question what it takes to define a correct probabilistic model for syntactic natural language processing. We focus on one particular theory of syntax, called dependency syntax, and develop a framework for developing probabilistic model for that linguistic theory. Subsequently, we review existing models of probabilistic dependency syntax and show some problematic aspects of these ...