Modeling coherence in text has been a task that has excited NLP researchers since a long time. It has applications in detecting incoherent structures and helping the author fix them. There has been recent work in using neural networks to extract a skeleton from one sentence, and then use that skeleton to generate the next sentence for coherent narrative story generation. In this project, we aim to study if the consistency of skeletons across subsequent sentences is a good metric to characterize the coherence of a given body of text. We propose a new Sentence/Skeleton Similarity Network (SSN) for modeling coherence across pairs of sentences, and show that this network performs much better than baseline similarity techniques like cosine similarity and Euclidean distance. Although skeletons appear to be promising candidates for modeling coherence, our results show that sentence-level models outperform those on skeletons for evaluating textual coherence, thus indicating that the current state-of-the-art coherence modeling techniques are going in the right direction by dealing with sentences rather than their sub-parts.
Agenda-based Narrative Extraction: Steering Pathfinding Algorithms with Large Language Models
Department of Computing and Systems Engineering, Universidad Católica del Norte, Antofagasta, Chile(智利天主教大学北部校区计算与系统工程系,安托法加斯塔,智利);Department of Industrial Engineering, Universidad Católica del Norte, Antofagasta, Chile(智利天主教大学北部校区工业工程系,安托法加斯塔,智利);Department of Chemical and Environmental Engineering, Universidad Católica del Norte, Antofagasta, Chile(智利天主教大学北部校区化学与环境工程系,安托法加斯塔,智利)
LitVISTA: A Benchmark for Narrative Orchestration in Literary Text
Institute of Information Engineering, Chinese Academy of Sciences(中国科学院信息工程研究所);School of Cyber Security, University of Chinese Academy of Sciences(中国科学院大学网络安全学院);University of Science and Technology of China(中国科学技术大学);University of Melbourne(墨尔本大学)
The Challenge and Reward of Fair Play in Narrative: A Computational Approach
Department of Computer Science Hebrew University of Jerusalem(计算机科学系 Hebrew University of Jerusalem);Department of Law and Digital Humanities Hebrew University of Jerusalem(法律与数字人文系 Hebrew University of Jerusalem)
STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences(中国科学院深圳先进技术研究院);University of Chinese Academy of Sciences(中国科学院大学);UNSW Sydney(新南威尔士大学);Chongqing University(重庆大学)