Abstract Language model pre-training has been shown to capture a surprising amount of
world knowledge, crucial for NLP tasks such as question answering. However, this …

Recent work on open domain question answering (QA) assumes strong supervision of the
supporting evidence and/or assumes a blackbox information retrieval (IR) system to retrieve …

We present SpanBERT, a pre-training method that is designed to better represent and
predict spans of text. Our approach extends BERT by (1) masking contiguous random spans …

Aspect based sentiment analysis (ABSA) involves three fundamental subtasks: aspect term
extraction, opinion term extraction, and aspect-level sentiment classification. Early works …

Current end-to-end machine reading and question answering (Q\&A) models are primarily
based on recurrent neural networks (RNNs) with attention. Despite their success, these …

We introduce the first end-to-end coreference resolution model and show that it significantly
outperforms all previous work without using a syntactic parser or hand-engineered mention …

In this paper, we present the gated self-matching networks for reading comprehension style
question answering, which aims to answer questions from a given passage. We first match …

We show that relation extraction can be reduced to answering simple reading
comprehension questions, by associating one or more natural-language questions with …

To obtain, deterministic guarantees of adversarial robustness, specialized training methods
are used. We propose, SABR, a novel such certified training method, based on the key …

Open-domain targeted sentiment analysis aims to detect opinion targets along with their
sentiment polarities from a sentence. Prior work typically formulates this task as a sequence …