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Authorship Verification
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Authorship verification (AV) is a research subject in the field of digital text forensics that concerns itself with the question, whether two documents have been written by the same person.
Definition taken from the paper Assessing the Applicability of Authorship Verification Methods, available at: https://arxiv.org/abs/1906.10551
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Human-AI Collaboration or Academic Misconduct? Measuring AI Use in Student Writing Through Stylometric Evidence
Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification
Tokenization is Sensitive to Language Variation
The \textit{Questio de aqua et terra}: A Computational Authorship Verification Study
Sui Generis: Large Language Models for Authorship Attribution and Verification in Latin
Addressing Topic Leakage in Cross-Topic Evaluation for Authorship Verification
InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verification
CAVE: Controllable Authorship Verification Explanations
Improving Quotation Attribution with Fictional Character Embeddings
Exploration of Masked and Causal Language Modelling for Text Generation
Forging the Forger: An Attempt to Improve Authorship Verification via Data Augmentation
Can Large Language Models Identify Authorship?
Authorship Verification based on the Likelihood Ratio of Grammar Models
Distinguishing Fictional Voices: a Study of Authorship Verification Models for Quotation Attribution
Can Authorship Attribution Models Distinguish Speakers in Speech Transcripts?
Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective
Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification
IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements
ICLEF: In-Context Learning with Expert Feedback for Explainable Style Transfer
Same or Different? Diff-Vectors for Authorship Analysis
On the State of the Art in Authorship Attribution and Authorship Verification
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web
Compromised account detection using authorship verification: a novel approach
Same Author or Just Same Topic? Towards Content-Independent Style Representations
Leveraging Ensembles and Self-Supervised Learning for Fully-Unsupervised Person Re-Identification and Text Authorship Attribution
Rethinking the Authorship Verification Experimental Setups
LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in Authorship Verification
Self-Calibrating Neural-Probabilistic Model for Authorship Verification Under Covariate Shift
Improving Authorship Verification using Linguistic Divergence
Datasets and Models for Authorship Attribution on Italian Personal Writings
Deep Bayes Factor Scoring for Authorship Verification
TAVeer: An Interpretable Topic-Agnostic Authorship Verification Method
MedLatinEpi and MedLatinLit: Two Datasets for the Computational Authorship Analysis of Medieval Latin Texts
A Step Towards Interpretable Authorship Verification
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