  The PAN 2021 authorship verification (AV) challenge is part of a three-year
strategy, moving from a cross-topic/closed-set AV task to a
cross-topic/open-set AV task over a collection of fanfiction texts. In this
work, we present a novel hybrid neural-probabilistic framework that is designed
to tackle the challenges of the 2021 task. Our system is based on our 2020
winning submission, with updates to significantly reduce sensitivities to
topical variations and to further improve the system's calibration by means of
an uncertainty-adaptation layer. Our framework additionally includes an
out-of-distribution detector (O2D2) for defining non-responses. Our proposed
system outperformed all other systems that participated in the PAN 2021 AV
task.
