The aim of multi-output learning is to simultaneously predict multiple outputs given an input.
It is an important learning problem for decision-making since making decisions in the real …

The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

PromptSource is a system for creating, sharing, and using natural language prompts.
Prompts are functions that map an example from a dataset to a natural language input and …

We introduce a multi-task setup of identifying and classifying entities, relations, and
coreference clusters in scientific articles. We create SciERC, a dataset that includes …

Cross-linguistically consistent annotation is necessary for sound comparative evaluation
and cross-lingual learning experiments. It is also useful for multilingual system development …

Biomedical text summarization is a critical task for comprehension of an ever-growing
amount of biomedical literature. Pre-trained language models (PLMs) with transformer …

While social media offer great communication opportunities, they also increase the
vulnerability of young people to threatening situations online. Recent studies report that …

This paper presents the first shared task on irony detection: given a tweet, automatic natural
language processing systems should determine whether the tweet is ironic (Task A) and …

This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis
(ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task …

Existing general clinical natural language processing (NLP) systems such as MetaMap and
Clinical Text Analysis and Knowledge Extraction System have been successfully applied to …