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This paper explores the relationship between routine-biased technological change and agglomeration economies. Using administrative data from Netherlands, we first show that in dense areas, jobs are less routine-task intensive (i.e. repetitive automatable), meaning cover a larger spectrum of tasks. We then explore how routine intensity affects urban wage premium. find premium is higher for worke...

1. ABSTRACT EVALITA is a recent initiative devoted to the evaluation of Natural Language and Speech Processing tools for Italian. The general objective of EVALITA is to promote the development of language and speech technologies for the Italian language, providing a shared framework where different systems and approaches can be evaluated in a consistent manner. In this work the results of the e...

One important challenge for cognitive systems research is to develop an integrated architecture that can enable effective, natural human-robot interactions in open worlds where new concepts, entities, and actions can be introduced through natural language during task performance. In this paper, we claim that in order to allow for such open-world tasking in natural language, all components in th...

The process engine for pattern recognition and information fusion tasks, the pepr framework, aims to empower the researcher to develop novel solutions in the field of pattern recognition and information fusion tasks in a timely manner, by supporting reuse and combination of well tested and established components in an environment, that eases the wiring of distinct algorithms and description of ...

Automatic evaluation for open-ended natural language generation tasks remains a challenge. We propose learned metric: Perception Score. It utilizes pre-trained model and considers context information conditional generation. Score assigns holistic score along with the uncertainty measurement. conduct experiments on three two unconditional tasks. achieves state-of-the-art results all consistently...

This open access book gives a deep overview of pre-trained language foundation models (BERT, GPT) and state-of-the-art for wide range NLP tasks