This paper documents and theoretically explains a nexus between globalization and residual wage inequality through internal labor market reorganization. Combining time-varying within-occupation task information from representative German labor force surveys with linked plant–worker data for Germany, we establish three interrelated facts: (1) Larger plants and exporters organize production into ...

Open Information Extraction (OIE) aims to automatically identify all the possible assertions within a sentence. Results of this task are usually a set of triples (subject, predicate, object). In this paper, we first present what OIE is and how it can be improved when we work in a given domain of knowledge. Using a corpus made up of sentences in building engineering construction, we obtain an im...

Semantic applications typically extract information from intermediate structures derived from sentences, such as dependency parse or semantic role labeling. In this paper, we study Open Information Extraction’s (Open IE) output as an additional intermediate structure and find that for tasks such as text comprehension, word similarity and word analogy it can be very effective. Specifically, for ...

In recent years interest in creating statistical automated text simplification systems has increased. Many of these systems have used parallel corpora of articles taken from Wikipedia and Simple Wikipedia or from Simple Wikipedia revision histories and generate Simple Wikipedia articles. In this work we motivate the need to construct a large, accessible corpus of everyday documents along with t...

A traditional deep neural network-based classifier assumes that only training classes appear during testing in closed-world settings. In most real-world applications, an open-set environment is more realistic than a conventional approach where unseen are potentially present the model’s lifetime. Open-set recognition (OSR) provides model with capability to address this issue by reducing risk, wh...

Table lookup with interpolation is used for many learning and adaptation tasks. Redundant mappings capture the important concept of "motor skill," which is important in real, behaving systems. Few, if any, robot skill implementations have dealt with redundant mappings, in which the space to be searched to create the table has much higher dimensionality than the table itself. A practical method ...

In the last years the use of the so-called bag-of-features approach, often referred to also as the codebook approach, has extensively gained large popularity among researchers in the image classification field, as it exhibited high levels of performance. A large variety of image classification, scene recognition, and more in general computer vision problems have been addressed according to this...