Consumption of media, and movies in particular, is increasing and is influenced by a
number of factors. One important and overlooked factor that affects the media consumption …

Evaluating Natural Language Generation (NLG) systems is a challenging task. Firstly, the
metric should ensure that the generated hypothesis reflects the reference's semantics …

The main task of an e-commerce search engine is to semantically match the user query to
the product inventory and retrieve the most relevant items that match the user's intent. This …

Generating knowledge grounded responses in both goal and non-goal oriented dialogue
systems is an important research challenge. Knowledge Graphs (KG) can be viewed as an …

Recent research has shown that multi-task pre-training greatly improves the model's
robustness and transfer ability, which is crucial for building a high-quality dialog system …

Many dialogue systems (DSs) lack characteristics humans have, such as emotion
perception, factuality, and informativeness. Enhancing DSs with knowledge alleviates this …

Building a universal conversational agent has been a long-standing goal of the dialogue
research community. Most previous works only focus on a small set of dialogue tasks. In this …

Dialogue agents can leverage external textual knowledge to generate responses of a higher
quality. To our best knowledge, most existing works on knowledge grounded dialogue …

Recently, neural network language models have been trained in an end-to-end and fully
data-driven manner, generating more flexible responses. Traditional neuro-language …

Here we discusses various topics related to natural language processing and question
answering systems. It explains the difference between reading comprehension QA and …