What is Wrong with Language Models that Can Not Tell a Story?

TL;DR

This paper highlights the critical lack of datasets, evaluation methods, and operational concepts for narrative processing, which impedes progress in NLP and AI's ability to generate meaningful, longer stories.

Contribution

It identifies key bottlenecks in narrative understanding and generation, emphasizing the need for foundational datasets and evaluation frameworks.

Findings

Current datasets are inadequate for narrative tasks

Evaluation methods for storytelling are lacking

Operational concepts for narrative processing are missing

Abstract

This paper argues that a deeper understanding of narrative and the successful generation of longer subjectively interesting texts is a vital bottleneck that hinders the progress in modern Natural Language Processing (NLP) and may even be in the whole field of Artificial Intelligence. We demonstrate that there are no adequate datasets, evaluation methods, and even operational concepts that could be used to start working on narrative processing.