Combating misinformation in the age of llms: Opportunities and challenges

C Chen, K Shu - AI Magazine, 2023 - Wiley Online Library
Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

A survey of text watermarking in the era of large language models

A Liu, L Pan, Y Lu, J Li, X Hu, X Zhang, L Wen… - ACM Computing …, 2024 - dl.acm.org
Text watermarking algorithms are crucial for protecting the copyright of textual content.
Historically, their capabilities and application scenarios were limited. However, recent …

Outfox: Llm-generated essay detection through in-context learning with adversarially generated examples

R Koike, M Kaneko, N Okazaki - … of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Large Language Models (LLMs) have achieved human-level fluency in text generation,
making it difficult to distinguish between human-written and LLM-generated texts. This poses …

A survey on llm-gernerated text detection: Necessity, methods, and future directions

J Wu, S Yang, R Zhan, Y Yuan, DF Wong… - arXiv preprint arXiv …, 2023 - arxiv.org
The powerful ability to understand, follow, and generate complex language emerging from
large language models (LLMs) makes LLM-generated text flood many areas of our daily …

A survey on detection of llms-generated content

X Yang, L Pan, X Zhao, H Chen, L Petzold… - arXiv preprint arXiv …, 2023 - arxiv.org
The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT
have led to an increase in synthetic content generation with implications across a variety of …

Detecting multimedia generated by large ai models: A survey

L Lin, N Gupta, Y Zhang, H Ren, CH Liu, F Ding… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid advancement of Large AI Models (LAIMs), particularly diffusion models and large
language models, has marked a new era where AI-generated multimedia is increasingly …

Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices

S Abdali, R Anarfi, CJ Barberan, J He - arXiv preprint arXiv:2403.12503, 2024 - arxiv.org
Large language models (LLMs) have significantly transformed the landscape of Natural
Language Processing (NLP). Their impact extends across a diverse spectrum of tasks …

AuthentiGPT: Detecting machine-generated text via black-box language models denoising

Z Guo, S Yu - arXiv preprint arXiv:2311.07700, 2023 - arxiv.org
Large language models (LLMs) have opened up enormous opportunities while
simultaneously posing ethical dilemmas. One of the major concerns is their ability to create …

Spotting llms with binoculars: Zero-shot detection of machine-generated text

A Hans, A Schwarzschild, V Cherepanova… - arXiv preprint arXiv …, 2024 - arxiv.org
Detecting text generated by modern large language models is thought to be hard, as both
LLMs and humans can exhibit a wide range of complex behaviors. However, we find that a …

Does\textsc {DetectGPT} Fully Utilize Perturbation? Selective Perturbation on Model-Based Contrastive Learning Detector would be Better

S Liu, X Liu, Y Wang, Z Cheng, C Li, Z Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
The burgeoning capabilities of large language models (LLMs) have raised growing
concerns about abuse. DetectGPT, a zero-shot metric-based unsupervised machine …