@inproceedings{86c57fa89463426dbec5aae351e3088d,
title = "Overview of the Cross-Domain Authorship Verification Task at PAN 2020",
abstract = "Copyright {\textcopyright} 2020 for this paper by its authors.Authorship identification remains a highly topical research problem in computational text analysis with many relevant applications in contemporary society and industry. For this edition of PAN, we focused on authorship verification, where the task is to assess whether a pair of documents has been authored by the same individual. Like in previous editions, we continued to work with (English-language) fanfiction, written by non-professional authors. As a novelty, we substantially increased the size of the provided dataset to enable more data-hungry approaches. In total, thirteen systems (from ten participating teams) have been submitted, which are substantially more diverse than the submissions from previous years. We provide a detailed comparison of these approaches and two generic baselines. Our findings suggest that the increased scale of the training data boosts the state of the art in the field, but we also confirm the conventional issue that the field struggles with an overreliance on topic-related information.",
author = "M. Kestemont and E. Manjavacas and I. Markov and J. Bevendorff and M. Wiegmann and E. Stamatatos and M. Potthast and B. Stein",
year = "2020",
language = "English",
volume = "2696",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS",
editor = "{De Carolis}, B. and C. Gena and A. Lieto and S. Rossi and A. Sciutti",
booktitle = "cAESAR 2020 - Proceedings of the Workshop on Adapted Interaction with Social Robots",
note = "11th Conference and Labs of the Evaluation Forum, CLEF 2020 ; Conference date: 22-09-2020 Through 25-09-2020",
}