Question answering (QA) systems provide a way of querying the information available in
various formats including, but not limited to, unstructured and structured data in natural …

Despite much progress in training artificial intelligence (AI) systems to imitate human
language, building agents that use language to communicate intentionally with humans in …

Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …

Abstract Generative Artificial Intelligence is set to revolutionize healthcare delivery by
transforming traditional patient care into a more personalized, efficient, and proactive …

Despite showing increasingly human-like conversational abilities, state-of-the-art dialogue
models often suffer from factual incorrectness and hallucination of knowledge (Roller et al …

Building open-domain chatbots is a challenging area for machine learning research. While
prior work has shown that scaling neural models in the number of parameters and the size of …

Challenging problems such as open-domain question answering, fact checking, slot filling
and entity linking require access to large, external knowledge sources. While some models …

We present a large, tunable neural conversational response generation model, DialoGPT
(dialogue generative pre-trained transformer). Trained on 147M conversation-like …

Practical applications of abstractive summarization models are limited by frequent factual
inconsistencies with respect to their input. Existing automatic evaluation metrics for …

Existing question answering (QA) datasets fail to train QA systems to perform complex
reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset …