There is essential information in the underlying structure of sentences and the relationships
between words and phrases in natural language questions, and the use of this information …

There is essential information in the underlying structure of words and phrases in natural
language questions, and this structure has been extensively studied. In this paper, we study …

An open-domain question answering (QA) system usually follows a retrieve-then-read
paradigm, in which a retriever is used to retrieve relevant passages from a large corpus, and …

We introduce question answering with a cotext in focus, a task that simulates a free
interaction with a QA system. The user reads on a screen some information about a topic …

For knowledge intensive NLP tasks, it has been widely accepted that accessing more
information is a contributing factor to improvements in the model's end-to-end performance …

Lexical matching remains the de facto evaluation method for open-domain question
answering (QA). Unfortunately, lexical matching fails completely when a plausible candidate …

Current methods in open-domain question answering (QA) usually employ a pipeline of first
retrieving relevant documents, then applying strong reading comprehension (RC) models to …

Abstract Research on Question Answering has produced an arsenal of useful techniques for
detecting answers that are explicitly present in the text of a collection of documents. To move …

Open-domain question answering is a challenging and fast-moving task in the field of
natural language processing. This paper provides an in-depth introduction to the problem …

We propose a simple and effective re-ranking method for improving passage retrieval in
open question answering. The re-ranker re-scores retrieved passages with a zero-shot …