Deciphering Textual Authenticity: A Generalized Strategy through the
Lens of Large Language Semantics for Detecting Human vs. Machine-Generated
Text

Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Text

17 January 2024

Mazal Bethany

Emet Bethany

Nishant Vishwamitra

Peyman Najafirad

Papers citing "Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Text"

3 / 3 papers shown

Title
MGTBench: Benchmarking Machine-Generated Text Detection Xinlei He Xinyue Shen Z. Chen Michael Backes Yang Zhang DeLMO 51 99 0 26 Mar 2023
Text and Code Embeddings by Contrastive Pre-Training Arvind Neelakantan Tao Xu Raul Puri Alec Radford Jesse Michael Han ... Tabarak Khan Toki Sherbakov Joanne Jang Peter Welinder Lilian Weng SSL AI4TS 204 412 0 24 Jan 2022
Artificial Text Detection via Examining the Topology of Attention Maps Laida Kushnareva D. Cherniavskii Vladislav Mikhailov Ekaterina Artemova S. Barannikov A. Bernstein Irina Piontkovskaya D. Piontkovski Evgeny Burnaev 31 48 0 10 Sep 2021