A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts
This paper presents a pioneering and comprehensive analysis of fake text, a pressing issue in the digital age, by categorizing it into two main types: Misinformation and LM-generated texts. It is the first study to systematically dissect and examine the intricate challenges and nuances in distinguis...
Saved in:
Main Authors: | Soonchan Kwon, Beakcheol Jang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10870239/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comprehensive Study on Zero-Shot Text Classification Using Category Mapping
by: Kai Zhang, et al.
Published: (2025-01-01) -
Optimized Novel Text Embedding Approach for Fake News Detection on Twitter X: Integrating Social Context, Temporal Dynamics, and Enhanced Interpretability
by: Mahmoud AlJamal, et al.
Published: (2025-02-01) -
Comparison of algorithms for the recognition of ChatGPT paraphrased texts
by: Aleksandar Kartelj, et al.
Published: (2025-02-01) -
Read. This. Slowly: mimicking spoken pauses in text messages
by: Rachel C. Poirier, et al.
Published: (2025-02-01) -
Enhancing Arabic text-to-speech synthesis for emotional expression in visually impaired individuals using the artificial hummingbird and hybrid deep learning model
by: Mahmoud M. Selim, et al.
Published: (2025-04-01)