Open-domain Question Answering (OpenQA) is an important task in Natural Language
Processing (NLP), which aims to answer a question in the form of natural language based …

Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural
Language Processing. The goal of this field is to develop systems for answering the …

Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

BERT model has been successfully applied to open-domain QA tasks. However, previous
work trains BERT by viewing passages corresponding to the same question as independent …

Retrieval-augmented generation models offer many benefits over standalone language
models: besides a textual answer to a given query they provide provenance items retrieved …

Although information access systems have long supportedpeople in accomplishing a wide
range of tasks, we propose broadening the scope of users of information access systems to …

With the swift growth of the information over the past few years, taking full benefit is
increasingly essential. Question Answering System is one of the promising methods to …

Question answering over RDF data like knowledge graphs has been greatly advanced, with
a number of good systems providing crisp answers for natural language questions or …

Direct answering of questions that involve multiple entities and relations is a challenge for
text-based QA. This problem is most pronounced when answers can be found only by …

Pickup and delivery problems with late penalties can be adopted to model a wide range of
practical situations in the field of transportation and logistics. However, the restrictions on the …