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 …

In conversational question answering, users express their information needs through a
series of utterances with incomplete context. Typical ConvQA methods rely on a single …

Building a skilled cybersecurity workforce is paramount to building a safer digital world.
However, the diverse skill set, constantly emerging vulnerabilities, and deployment of new …

Models for conversational question answering (ConvQA) over knowledge graphs (KGs) are
usually trained and tested on benchmarks of gold QA pairs. This implies that training is …

Advancements in natural language processing have revolutionized the way we can interact
with digital information systems, such as databases, making them more accessible …

Although Large Language Models (LLMs) are effective in performing various NLP tasks,
they still struggle to handle tasks that require extensive, real-world knowledge, especially …

In this paper we consider the task of conversational semantic parsing over general purpose
knowledge graphs (KGs) with millions of entities, and thousands of relation-types. We focus …

Conversational interfaces are increasingly used by websites and apps, including office
software as well as creativity tools. This trend reflects a shift towards natural language in …

In this study, we focus on the task of selecting high-quality answers selection in knowledge-
graph-based (KG-based) conversational question answering (ConvQA) system. Effectively …

This particular paper introduces an Adaptive Context Management (ACM) framework for the
Conversational Question Answering (ConvQA) systems. The key objective of the ACM …