The question answering system is frequently applied in the area of natural language
processing (NLP) because of the wide variety of applications. It consists of answering …

Transformer-based language models (TLMs) have widely been recognized to be a cutting-
edge technology for the successful development of deep-learning-based solutions to …

The core of information retrieval (IR) is to identify relevant information from large-scale
resources and return it as a ranked list to respond to user's information need. In recent years …

Heavily pre-trained transformer models such as BERT have recently shown to be
remarkably powerful at language modelling, achieving impressive results on numerous …

We investigate BERT in an evidence retrieval and claim verification pipeline for the task of
evidence-based claim verification. To this end, we propose to use two BERT models, one for …

Short text similarity plays an important role in natural language processing (NLP). It has
been applied in many fields. Due to the lack of sufficient context in the short text, it is difficult …

A table is composed of data values that are organized in rows and columns providing
implicit structural information. A table is usually accompanied by secondary information such …

Pretrained contextualized language models such as BERT have achieved impressive
results on various natural language processing benchmarks. Benefiting from multiple …

Emotions are vital for identifying an individual's attitude and mental condition. Detecting and
classifying emotions in Natural Language Processing applications can improve Human …

We focus on the task of Frequently Asked Questions (FAQ) retrieval. A given user query can
be matched against the questions and/or the answers in the FAQ. We present a fully …