Combating misinformation in the age of llms: Opportunities and challenges

C Chen, K Shu - AI Magazine, 2024 - 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 …

Trustllm: Trustworthiness in large language models

Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

Mgtbench: Benchmarking machine-generated text detection

X He, X Shen, Z Chen, M Backes, Y Zhang - Proceedings of the 2024 on …, 2024 - dl.acm.org
Nowadays, powerful large language models (LLMs) such as ChatGPT have demonstrated
revolutionary power in a variety of natural language processing (NLP) tasks such as text …

[HTML][HTML] Position: TrustLLM: Trustworthiness in large language models

Y Huang, L Sun, H Wang, S Wu… - International …, 2024 - proceedings.mlr.press
Large language models (LLMs) have gained considerable attention for their excellent
natural language processing capabilities. Nonetheless, these LLMs present many …

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 …

A Survey of Confidence Estimation and Calibration in Large Language Models

J Geng, F Cai, Y Wang, H Koeppl… - Proceedings of the …, 2024 - aclanthology.org
Large language models (LLMs) have demonstrated remarkable capabilities across a wide
range of tasks in various domains. Despite their impressive performance, they can be …

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 …

Semstamp: A semantic watermark with paraphrastic robustness for text generation

AB Hou, J Zhang, T He, Y Wang, YS Chuang… - arXiv preprint arXiv …, 2023 - arxiv.org
Existing watermarking algorithms are vulnerable to paraphrase attacks because of their
token-level design. To address this issue, we propose SemStamp, a robust sentence-level …

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 …