Image de couverture de livre

AIDetx: a compression-based method for identification of machine-learning generated text

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Almeida, Leonardo, Rodrigues, Pedro, Magalhães, Diogo, Pinho, Armando J., Pratas, Diogo
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Decoding the Past: Explainable Machine Learning Models for Dating Historical Texts
par: Pinto, Paulo J. N., et autres
Publié: (2025)

LLM-based feature generation from text for interpretable machine learning
par: Balek, Vojtěch, et autres
Publié: (2024)

An experimental sorting method for improving metagenomic data encoding
par: Pratas, Diogo, et autres
Publié: (2024)

Extractive text summarisation of Privacy Policy documents using machine learning approaches
par: Choi, Chanwoo
Publié: (2024)

Text classification using machine learning methods
par: Oancea, Bogdan
Publié: (2025)

Performance of diverse evaluation metrics in NLP-based assessment and text generation of consumer complaints
par: Gao, Peiheng, et autres
Publié: (2025)

Machine-generated text detection prevents language model collapse
par: Drayson, George, et autres
Publié: (2025)

Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach
par: Pernes, Diogo, et autres
Publié: (2024)

Questionable practices in machine learning
par: Leech, Gavin, et autres
Publié: (2024)

Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language Modeling
par: Belkadi, Samuel, et autres
Publié: (2024)

ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs
par: Vieira, Inês, et autres
Publié: (2026)

"Show Me What's Wrong!": Combining Charts and Text to Guide Data Analysis
par: Feliciano, Beatriz, et autres
Publié: (2024)

Private prediction for large-scale synthetic text generation
par: Amin, Kareem, et autres
Publié: (2024)

Stylometry recognizes human and LLM-generated texts in short samples
par: Przystalski, Karol, et autres
Publié: (2025)

When Refusals Fail: Unstable Safety Mechanisms in Long-Context LLM Agents
par: Hadeliya, Tsimur, et autres
Publié: (2025)

A meta-analysis on the performance of machine-learning based language models for sentiment analysis
par: Rohde, Elena, et autres
Publié: (2025)

An energy-based comparative analysis of common approaches to text classification in the Legal domain
par: Gultekin, Sinan, et autres
Publié: (2023)

Enhancing ASD detection accuracy: a combined approach of machine learning and deep learning models with natural language processing
par: Rubio-Martín, Sergio, et autres
Publié: (2024)

Rethinking harmless refusals when fine-tuning foundation models
par: Pop, Florin, et autres
Publié: (2024)

A data science and machine learning approach to continuous analysis of Shakespeare's plays
par: Swisher, Charles, et autres
Publié: (2023)

Momentum Point-Perplexity Mechanics in Large Language Models
par: Tomaz, Lorenzo, et autres
Publié: (2025)

Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literature
par: Zhou, Sijia, et autres
Publié: (2024)

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods
par: Jang, Yeonwoo, et autres
Publié: (2025)

Evil twins are not that evil: Qualitative insights into machine-generated prompts
par: Rakotonirina, Nathanaël Carraz, et autres
Publié: (2024)

On the evolution of research in hypersonics: application of natural language processing and machine learning
par: Ebadi, Ashkan, et autres
Publié: (2022)

AtteSTNet -- An attention and subword tokenization based approach for code-switched text hate speech detection
par: Shingi, Geet, et autres
Publié: (2021)

Explainable machine learning multi-label classification of Spanish legal judgements
par: de Arriba-Pérez, Francisco, et autres
Publié: (2024)

Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
par: Benítez-Andrades, José Alberto, et autres
Publié: (2024)

Deep learning models for representing out-of-vocabulary words
par: Lochter, Johannes V., et autres
Publié: (2020)

Dissecting embedding method: learning higher-order structures from data
par: Tupikina, Liubov, et autres
Publié: (2024)

Generating Multidimensional Clusters With Support Lines
par: Fachada, Nuno, et autres
Publié: (2023)

Krony-PT: GPT2 compressed with Kronecker Products
par: Ayad, Mohamed Ayoub Ben, et autres
Publié: (2024)

The study of short texts in digital politics: Document aggregation for topic modeling
par: Nakka, Nitheesha, et autres
Publié: (2025)

Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing
par: Liu, Shengchao, et autres
Publié: (2022)

Effects of term weighting approach with and without stop words removing on Arabic text classification
par: Alhenawi, Esra'a, et autres
Publié: (2024)

Understanding the learned look-ahead behavior of chess neural networks
par: Cruz, Diogo
Publié: (2025)

Critical biblical studies via word frequency analysis: unveiling text authorship
par: Faigenbaum-Golovin, Shira, et autres
Publié: (2024)

Cropping outperforms dropout as an augmentation strategy for self-supervised training of text embeddings
par: González-Márquez, Rita, et autres
Publié: (2025)

A comparison of data filtering techniques for English-Polish LLM-based machine translation in the biomedical domain
par: Lérida, Jorge del Pozo, et autres
Publié: (2025)

Qwen it detect machine-generated text?
par: Marchitan, Teodor-George, et autres
Publié: (2025)