Question answering (QA) is a fundamental means to facilitate assessment and training of
narrative comprehension skills for both machines and young children, yet there is scarcity of …

Narrative understanding involves capturing the author's cognitive processes, providing
insights into their knowledge, intentions, beliefs, and desires. Although large language …

Existing question answering (QA) techniques are created mainly to answer questions asked
by humans. But in educational applications, teachers often need to decide what questions …

With the ubiquitous use of online meeting platforms and robust automatic speech
recognition systems, meeting transcripts have emerged as a promising domain for natural …

We propose a new task for assessing machines' skills of understanding fictional characters
in narrative stories. The task, TVShowGuess, builds on the scripts of TV series and takes the …

Everyday news coverage has shifted from traditional broadcasts towards a wide range of
presentation formats such as first-hand, unedited video footage. Datasets that reflect the …

Comprehending characters' personalities is a crucial aspect of story reading. As readers
engage with a story, their understanding of a character evolves based on new events and …

Abstract Narrative Why-Question Answering is an important task to assess the causal
reasoning ability of systems in narrative settings. Further progress in this domain needs …

Human-annotated labels and explanations are critical for training explainable NLP models.
However, unlike human-annotated labels whose quality is easier to calibrate (eg, with a …

As the body of research on machine narrative comprehension grows, there is a critical need
for consideration of performance assessment strategies as well as the depth and scope of …