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A method for authorship attribution based on function word adjacency networks (WANs) is introduced. Function words are parts of speech that express grammatical relationships between other words but do not carry lexical meaning on their own.…

Computation and Language · Computer Science 2015-10-28 Santiago Segarra , Mark Eisen , Alejandro Ribeiro

The recent surge in high-quality open-source Generative AI text models (colloquially: LLMs), as well as efficient finetuning techniques, have opened the possibility of creating high-quality personalized models that generate text attuned to…

Computation and Language · Computer Science 2025-06-03 Eugenia Iofinova , Andrej Jovanovic , Dan Alistarh

Quasi-identifier-based deidentification techniques (QI-deidentification) are widely used in practice, including $k$-anonymity, $\ell$-diversity, and $t$-closeness. We present three new attacks on QI-deidentification: two theoretical attacks…

Cryptography and Security · Computer Science 2022-03-01 Aloni Cohen

Explanations in Computer Vision are often desired, but most Deep Neural Networks can only provide saliency maps with questionable faithfulness. Self-Explaining Neural Networks (SENN) extract interpretable concepts with fidelity, diversity,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Thomas Norrenbrock , Marco Rudolph , Bodo Rosenhahn

With the overwhelming success in the field of quantum information in the last decades, the "quest" for a Quantum Neural Network (QNN) model began in order to combine quantum computing with the striking properties of neural computing. This…

Quantum Physics · Physics 2014-09-01 M. Schuld , I. Sinayskiy , F. Petruccione

The power of natural language generation models has provoked a flurry of interest in automatic methods to detect if a piece of text is human or machine-authored. The problem so far has been framed in a standard supervised way and consists…

Computation and Language · Computer Science 2021-11-05 Matthias Gallé , Jos Rozen , Germán Kruszewski , Hady Elsahar

Watkins' and Dayan's Q-learning is a model-free reinforcement learning algorithm that iteratively refines an estimate for the optimal action-value function of an MDP by stochastically "visiting" many state-ation pairs [Watkins and Dayan,…

Machine Learning · Computer Science 2021-08-09 Matthew T. Regehr , Alex Ayoub

In this work we consider the impact of information spread in time-varying social networks, where agents request to follow other agents with aligned opinions while dropping ties to neighbors whose posts are too dissimilar to their own views.…

Social and Information Networks · Computer Science 2024-03-28 Michael DeBuse , Sean Warnick

AI-generated text is proliferating across domains, from creative writing and journalism to marketing content and scientific articles. Models can follow user-provided instructions to generate coherent and grammatically correct outputs but in…

Computation and Language · Computer Science 2025-08-14 Tuhin Chakrabarty , Philippe Laban , Chien-Sheng Wu

Author profiling, the analysis of texts to uncover attributes such as gender and age of the author, has become essential with the widespread use of social media platforms. This paper focuses on author profiling in the Bangla language,…

Computation and Language · Computer Science 2024-12-04 Raisa Tasnim , Mehanaz Chowdhury , Md Ataur Rahman

Authorship attribution is a natural language processing task that has been widely studied, often by considering small order statistics. In this paper, we explore a complex network approach to assign the authorship of texts based on their…

Computation and Language · Computer Science 2017-08-08 Vanessa Q. Marinho , Henrique F. de Arruda , Thales S. Lima , Luciano F. Costa , Diego R. Amancio

The Q-learning algorithm is known to be affected by the maximization bias, i.e. the systematic overestimation of action values, an important issue that has recently received renewed attention. Double Q-learning has been proposed as an…

Machine Learning · Computer Science 2021-02-03 Rong Zhu , Mattia Rigotti

We study the degree to which a character string, $Q$, leaks details about itself any time it engages in comparison protocols with a strings provided by a querier, Bob, even if those protocols are cryptographically guaranteed to produce no…

Data Structures and Algorithms · Computer Science 2016-11-15 Michael T. Goodrich

AI-generated text has proliferated across various online platforms, offering both transformative prospects and posing significant risks related to misinformation and manipulation. Addressing these challenges, this paper introduces SAID…

Computation and Language · Computer Science 2023-10-13 Wanyun Cui , Linqiu Zhang , Qianle Wang , Shuyang Cai

Deep neural networks (DNNs) have achieved tremendous success in computer vision, natural language processing, and scientific and engineering domains. However, DNNs can make unexpected, incorrect, yet overconfident predictions, leading to…

Machine Learning · Computer Science 2025-12-16 Wenchong He , Zhe Jiang , Tingsong Xiao , Zelin Xu , Yukun Li

Authorship style transfer involves altering text to match the style of a target author whilst preserving the original meaning. Existing unsupervised approaches like STRAP have largely focused on style transfer to target authors with many…

Computation and Language · Computer Science 2024-11-05 Ajay Patel , Nicholas Andrews , Chris Callison-Burch

Positive feedback via likes and awards is central to online governance, yet which attributes of users' posts elicit rewards -- and how these vary across authors and communities -- remains unclear. To examine this, we combine…

Human-Computer Interaction · Computer Science 2026-02-03 Agam Goyal , Charlotte Lambert , Eshwar Chandrasekharan

The automatic quality assessment of self-media online articles is an urgent and new issue, which is of great value to the online recommendation and search. Different from traditional and well-formed articles, self-media online articles are…

Computation and Language · Computer Science 2020-08-14 Yiru Wang , Shen Huang , Gongfu Li , Qiang Deng , Dongliang Liao , Pengda Si , Yujiu Yang , Jin Xu

In recent years, messages and text posted on the Internet are used in criminal investigations. Unfortunately, the authorship of many of them remains unknown. In some channels, the problem of establishing authorship may be even harder, since…

Computation and Language · Computer Science 2020-10-19 Nicole Mariah Sharon Belvisi , Naveed Muhammad , Fernando Alonso-Fernandez

Authorship attribution is the problem of identifying the most plausible author of an anonymous text from a set of candidate authors. Researchers have investigated same-topic and cross-topic scenarios of authorship attribution, which differ…

Computation and Language · Computer Science 2021-09-10 Malik H. Altakrori , Jackie Chi Kit Cheung , Benjamin C. M. Fung
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