Eighth International Workshop on Narrative Extraction from Texts
held in conjunction with the 47th European Conference on Information Retrieval
For seven years, the Text2Story Workshop series has fostered a vibrant community dedicated to understanding narrative structure in text, resulting in significant contributions to the field and developing a shared understanding of the challenges in this domain. While traditional methods have yielded valuable insights, the advent of Transformers and LLMs have ignited a new wave of interest in narrative understanding. In the eighth edition of the Text2Story workshop, we propose to go deeper into the role of LLMs in narrative understanding exploring the issues involved in using LLMs to unravel narrative structures, while also examining the characteristics of narratives generated by LLMs. By fostering dialogue on these emerging areas, we aim to identify the wide-ranging issues related to the narrative extraction task and continue the workshop's tradition of driving innovation in narrative understanding research.
Research works submitted to the workshop should advance the scientific understanding of all aspects of narrative extraction from texts. This includes, but is not limited to, topics such as narrative information extraction, formal representation of narratives, narrative analysis and generation, development of datasets and evaluation protocols, as well as ethics and bias in narratives, and narrative applications. We encourage the submission of high-quality and original submissions covering the following topics and contributions focused on low and medium-resource languages.
We solicit the following types of contributions:
Original and high-quality unpublished contributions to the theory and practical aspects of the narrative extraction task. Full papers should introduce existing approaches, describe the methodology and the experiments conducted in detail. Negative result papers to highlight tested hypotheses that did not get the expected outcome are also welcomed.
Unpublished short papers describing work in progress; position papers introducing a new point of view, a research vision or a reasoned opinion on the workshop topics; and dissemination papers describing project ideas, ongoing research lines, case studies or summarized versions of previously published papers in high-quality conferences/journals that is worthwhile sharing with the Text2Story community, but where novelty is not a fundamental issue.
Unpublished papers presenting research/industrial demos; papers describing important resources (datasets or software packages) to the Text2Story community;
Papers must be submitted electronically in PDF format through Easy Chair . All submissions must be in English and formatted according to the one-column CEUR-ART style with no page numbers. Templates, either in Word or LaTeX, can be found in the following zip folder . There is also an Overleaf page for LaTeX users.
IMPORTANT: Please include between brackets the type of submission (full; negative results; work in progress; demo and resource; position; dissemination) in the paper title.
Papers submitted to Text2Story 2025 should be original work and different from papers that have been previously published, accepted for publication, or that are under review at other venues. Exceptions to this rule are "dissemination papers". Pre-prints submitted to ArXiv are eligible.
All papers will be refereed through a double-blind peer-review process by at least two members of the programme committee. The accepted papers will appear in the proceedings published at CEUR workshop proceedings (indexed in Scopus and DBLP) as long as they don't conflict with previous publication rights.
Text2Story 2025 will be held at the 47th European Conference on Information Retrieval (ECIR'25) in Lucca, Italy
Registration at ECIR 2025 is required to attend the workshop (don't forget to select the Text2Story workshop).
This work is financed by National Funds through the FCT - Fundação para a Ciência e a Tecnologia, I.P. (Portuguese Foundation for Science and Technology) within the project StorySense, with reference 2022.09312.PTDC (DOI 10.54499/2022.09312.PTDC).
