Imagen de Portada

Transformer and Hybrid Deep Learning Based Models for Machine-Generated Text Detection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Marchitan, Teodor-George, Creanga, Claudiu, Dinu, Liviu P.
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Few-shot text-based emotion detection
por: Marchitan, Teodor-George, et al.
Publicado: (2025)

Qwen it detect machine-generated text?
por: Marchitan, Teodor-George, et al.
Publicado: (2025)

Transformer based neural networks for emotion recognition in conversations
por: Creanga, Claudiu, et al.
Publicado: (2024)

Automated Text Identification Using CNN and Training Dynamics
por: Creanga, Claudiu, et al.
Publicado: (2024)

Designing NLP Systems That Adapt to Diverse Worldviews
por: Creanga, Claudiu, et al.
Publicado: (2024)

The Art That Poses Back: Assessing AI Pastiches after Contemporary Artworks
por: Dinu, Anca, et al.
Publicado: (2026)

PsihoRo: Depression and Anxiety Romanian Text Corpus
por: Ciobotaru, Alexandra, et al.
Publicado: (2026)

Measuring cross-language intelligibility between Romance languages with computational tools
por: Dinu, Liviu P, et al.
Publicado: (2026)

Datasets for Depression Modeling in Social Media: An Overview
por: Bucur, Ana-Maria, et al.
Publicado: (2025)

On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook
por: Bucur, Ana-Maria, et al.
Publicado: (2024)

Detecting AI Generated Text Based on NLP and Machine Learning Approaches
por: Prova, Nuzhat
Publicado: (2024)

Assessing Classical Machine Learning and Transformer-based Approaches for Detecting AI-Generated Research Text
por: Parimanoharan, Sharanya, et al.
Publicado: (2025)

Exploring the Limitations of Detecting Machine-Generated Text
por: Doughman, Jad, et al.
Publicado: (2024)

Applying Ensemble Methods to Model-Agnostic Machine-Generated Text Detection
por: Ong, Ivan, et al.
Publicado: (2024)

ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability
por: Koike, Ryuto, et al.
Publicado: (2025)

Large Language Models Can Self-Improve At Web Agent Tasks
por: Patel, Ajay, et al.
Publicado: (2024)

MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detection
por: Puspo, Sadiya Sayara Chowdhury, et al.
Publicado: (2024)

Multi-Level Contextual Token Relation Modeling for Machine-Generated Text Detection
por: Wu, Chenwang, et al.
Publicado: (2026)

Cheap Ways of Extracting Clinical Markers from Texts
por: Sandu, Anastasia, et al.
Publicado: (2024)

Authorship Obfuscation in Multilingual Machine-Generated Text Detection
por: Macko, Dominik, et al.
Publicado: (2024)

AI-Generated Text Detection and Classification Based on BERT Deep Learning Algorithm
por: Wang, Hao, et al.
Publicado: (2024)

Sharif-MGTD at SemEval-2024 Task 8: A Transformer-Based Approach to Detect Machine Generated Text
por: Ebrahimi, Seyedeh Fatemeh, et al.
Publicado: (2024)

DeepPavlov at SemEval-2024 Task 8: Leveraging Transfer Learning for Detecting Boundaries of Machine-Generated Texts
por: Voznyuk, Anastasia, et al.
Publicado: (2024)

EMMM, Explain Me My Model! Explainable Machine Generated Text Detection in Dialogues
por: Yuan, Angela Yifei, et al.
Publicado: (2025)

Detection of Machine-Generated Text: Literature Survey
por: Valiaiev, Dmytro
Publicado: (2024)

AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models
por: Guggilla, Chinnappa, et al.
Publicado: (2025)

Hybrid Machine Learning Model for Detecting Bangla Smishing Text Using BERT and Character-Level CNN
por: Tanbhir, Gazi, et al.
Publicado: (2025)

A Comparative Approach to Assessing Linguistic Creativity of Large Language Models and Humans
por: Dinu, Anca, et al.
Publicado: (2025)

LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection
por: Abassy, Mervat, et al.
Publicado: (2024)

Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers
por: Gong, Linyuan, et al.
Publicado: (2023)

T-Detect: Tail-Aware Statistical Normalization for Robust Detection of Adversarial Machine-Generated Text
por: West, Alva, et al.
Publicado: (2025)

Learning to Rewrite: Generalized LLM-Generated Text Detection
por: Li, Ran, et al.
Publicado: (2024)

Mixture of Detectors: A Compact View of Machine-Generated Text Detection
por: Lekkala, Sai Teja, et al.
Publicado: (2025)

Social Media Sentiments Analysis on the July Revolution in Bangladesh: A Hybrid Transformer Based Machine Learning Approach
por: Hossen, Md. Sabbir, et al.
Publicado: (2025)

Detecting Racist Text in Bengali: An Ensemble Deep Learning Framework
por: Saruar, S. S., et al.
Publicado: (2024)

LM$^2$otifs : An Explainable Framework for Machine-Generated Texts Detection
por: Zheng, Xu, et al.
Publicado: (2025)

Beyond instruction-conditioning, MoTE: Mixture of Task Experts for Multi-task Embedding Models
por: Romero, Miguel, et al.
Publicado: (2025)

TextMachina: Seamless Generation of Machine-Generated Text Datasets
por: Sarvazyan, Areg Mikael, et al.
Publicado: (2024)

Monocle: Hybrid Local-Global In-Context Evaluation for Long-Text Generation with Uncertainty-Based Active Learning
por: Wang, Xiaorong, et al.
Publicado: (2025)

DetectAnyLLM: Towards Generalizable and Robust Detection of Machine-Generated Text Across Domains and Models
por: Fu, Jiachen, et al.
Publicado: (2025)