Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …

In the NLP community, recent years have seen a surge of research activities that address
machines' ability to perform deep language understanding which goes beyond what is …

We present a large-scale collection of diverse natural language inference (NLI) datasets that
help provide insight into how well a sentence representation captures distinct types of …

Despite recent advances in information retrieval and natural language processing, rhetorical
devices that exploit ambiguity or subvert linguistic rules remain a challenge for such …

This paper describes the SemEval-2020 shared task" Assessing Humor in Edited News
Headlines." The task's dataset contains news headlines in which short edits were applied to …

We introduce, release, and analyze a new dataset, called Humicroedit, for research in
computational humor. Our publicly available data consists of regular English news …

While humour and wordplay are among the most intensively studied problems in the field of
translation studies, they have been almost completely ignored in machine translation. This is …

Humor is a substantial element of human social behavior, affect, and cognition. Its automatic
understanding can facilitate a more naturalistic human-AI interaction. Current methods of …

The goal of the JOKER track series is to bring together linguists, translators, and computer
scientists to foster progress on the automatic interpretation, generation, and translation of …