mlsanityData to 7 Oct 2026

O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in Authorship Verification

arXiv 2106.15825 ↗First posted 30 Jun 2021cs.CLcited by 6

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Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 11 of its 20 references that are in the map. First posted on arXiv 30 Jun 2021.

Builds on

11 of 20 references.

References · 11

  1. 2017On Calibration of Modern Neural Networkscited by 4,860
  2. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,888
  3. 2015Domain-Adversarial Training of Neural Networkscited by 3,023
  4. 2017What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?cited by 2,335
  5. 2017Regularizing Neural Networks by Penalizing Confident Output Distributionscited by 461
  6. 2019Explainable Authorship Verification in Social Media via Attention-based Similarity Learningcited by 36
  7. 2020The Importance of Suppressing Domain Style in Authorship Analysiscited by 18
  8. 2017Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrixcited by 14
  9. 2020Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasetscited by 7
  10. 2020Deep Bayes Factor Scoring for Authorship Verificationcited by 7
  11. 2021Self-Calibrating Neural-Probabilistic Model for Authorship Verification Under Covariate Shiftcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 1; 2025: 0; 2026: 1.

6 papers.

  1. 2022On the State of the Art in Authorship Attribution and Authorship Verificationcited by 27
  2. 2022VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Webcited by 10
  3. 2021Rethinking the Authorship Verification Experimental Setupscited by 5
  4. 2024Addressing Topic Leakage in Cross-Topic Evaluation for Authorship Verificationcited by 2
  5. 2023Authorship identification under domain shift: a survey of stylistic measures and learned author representationscited by 1
  6. 2026Contrastive Learning for Authorship Verificationcited by 0