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 …

On the trustworthiness landscape of state-of-the-art generative models: A comprehensive survey

M Fan, C Chen, C Wang, J Huang - arXiv preprint arXiv:2307.16680, 2023 - arxiv.org
Diffusion models and large language models have emerged as leading-edge generative
models and have sparked a revolutionary impact on various aspects of human life. However …

Fast-detectgpt: Efficient zero-shot detection of machine-generated text via conditional probability curvature

G Bao, Y Zhao, Z Teng, L Yang, Y Zhang - arXiv preprint arXiv:2310.05130, 2023 - arxiv.org
Large language models (LLMs) have shown the ability to produce fluent and cogent content,
presenting both productivity opportunities and societal risks. To build trustworthy AI systems …

Dna-gpt: Divergent n-gram analysis for training-free detection of gpt-generated text

X Yang, W Cheng, Y Wu, L Petzold, WY Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have notably enhanced the fluency and diversity of machine-
generated text. However, this progress also presents a significant challenge in detecting the …

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 …

Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews

W Liang, Z Izzo, Y Zhang, H Lepp, H Cao… - arXiv preprint arXiv …, 2024 - arxiv.org
We present an approach for estimating the fraction of text in a large corpus which is likely to
be substantially modified or produced by a large language model (LLM). Our maximum …

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 …

Adaptive ensembles of fine-tuned transformers for llm-generated text detection

Z Lai, X Zhang, S Chen - arXiv preprint arXiv:2403.13335, 2024 - arxiv.org
Large language models (LLMs) have reached human-like proficiency in generating diverse
textual content, underscoring the necessity for effective fake text detection to avoid potential …