M4: Multi-generator, multi-domain, and multi-lingual black-box machine-generated text detection

Y Wang, J Mansurov, P Ivanov, J Su… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have demonstrated remarkable capability to generate fluent
responses to a wide variety of user queries. However, this has also raised concerns about …

Overview of the “voight-kampff” generative AI authorship verification task at PAN and ELOQUENT 2024

J Bevendorff, M Wiegmann, J Karlgren… - 25th Working Notes of …, 2024 - diva-portal.org
Abstract The “Voight-Kampff” Generative AI Authorship Verification task aims to determine
whether a text was generated by an AI or written by a human. As in its fictional inspiration, 1 …

Overview of iberautextification at iberlef 2024: Detection and attribution of machine-generated text on languages of the iberian peninsula

AM Sarvazyan, JÁ González, F Rangel… - … del Lenguaje Natural, 2024 - riunet.upv.es
[EN] This paper presents the overview of the IberAuTexTification shared taskas part of the
IberLEF 2024 Workshop in Iberian Languages Evaluation Forum, within the framework of …

Llm-detectaive: a tool for fine-grained machine-generated text detection

M Abassy, K Elozeiri, A Aziz, MN Ta, RV Tomar… - arXiv preprint arXiv …, 2024 - arxiv.org
The ease of access to large language models (LLMs) has enabled a widespread of machine-
generated texts, and now it is often hard to tell whether a piece of text was human-written or …

A Survey on Automatic Credibility Assessment of Textual Credibility Signals in the Era of Large Language Models

I Srba, O Razuvayevskaya, JA Leite, R Moro… - arXiv preprint arXiv …, 2024 - arxiv.org
In the current era of social media and generative AI, an ability to automatically assess the
credibility of online social media content is of tremendous importance. Credibility …

Robust ai-generated text detection by restricted embeddings

K Kuznetsov, E Tulchinskii, L Kushnareva… - arXiv preprint arXiv …, 2024 - arxiv.org
Growing amount and quality of AI-generated texts makes detecting such content more
difficult. In most real-world scenarios, the domain (style and topic) of generated data and the …

[PDF][PDF] A verifying generative text authorship model with regularized dropout

Z Lin, Z Han, L Kong, M Chen, S Zhang, J Peng… - Working Notes of …, 2024 - ceur-ws.org
Generative AI authorship verification aims to identify the text authored by a human within a
given pair of texts. This paper presents our method for the PAN 2024 Generative AI …

Genaios at semeval-2024 task 8: Detecting machine-generated text by mixing language model probabilistic features

AM Sarvazyan, JÁ González… - Proceedings of the 18th …, 2024 - aclanthology.org
This paper describes the participation of the Genaios team in the monolingual track of
Subtask A at SemEval-2024 Task 8. Our best system, LLMixtic, is a Transformer Encoder …

DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning

X Guo, S Zhang, Y He, T Zhang, W Feng… - arXiv preprint arXiv …, 2024 - arxiv.org
Current techniques for detecting AI-generated text are largely confined to manual feature
crafting and supervised binary classification paradigms. These methodologies typically lead …

Beemo: Benchmark of Expert-edited Machine-generated Outputs

E Artemova, J Lucas, S Venkatraman, J Lee… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid proliferation of large language models (LLMs) has increased the volume of
machine-generated texts (MGTs) and blurred text authorship in various domains. However …