Abstract Open-domain Question Answering models that directly leverage question-answer
(QA) pairs, such as closed-book QA (CBQA) models and QA-pair retrievers, show promise in …

Document-level relation extraction aims to extract relations among multiple entity pairs from
a document. Previously proposed graph-based or transformer-based models utilize the …

Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks,
eg, part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc …

Recent years have seen the paradigm shift of Named Entity Recognition (NER) systems
from sequence labeling to span prediction. Despite its preliminary effectiveness, the span …

A recent state-of-the-art neural open information extraction (OpenIE) system generates
extractions iteratively, requiring repeated encoding of partial outputs. This comes at a …

Analogies have been central to creative problem-solving throughout the history of science
and technology. As the number of scientific articles continues to increase exponentially …

In cross-lingual named entity recognition (NER), self-training is commonly used to bridge the
linguistic gap by training on pseudo-labeled target-language data. However, due to sub …

We study the problem of building entity tagging systems by using a few rules as weak
supervision. Previous methods mostly focus on disambiguation entity types based on …

Mining an argument structure from text is an important step for tasks such as argument
search and summarization. While studies on argument (ation) mining have proposed …

Abstract Information Extraction (IE) spans several tasks with different output structures, such
as named entity recognition, relation extraction and event extraction. Previously, those tasks …