[HTML][HTML] A survey on large language model (llm) security and privacy: The good, the bad, and the ugly

Y Yao, J Duan, K Xu, Y Cai, Z Sun, Y Zhang - High-Confidence Computing, 2024 - Elsevier
Abstract Large Language Models (LLMs), such as ChatGPT and Bard, have revolutionized
natural language understanding and generation. They possess deep language …

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 …

Llm evaluators recognize and favor their own generations

A Panickssery, S Bowman… - Advances in Neural …, 2025 - proceedings.neurips.cc
Self-evaluation using large language models (LLMs) has proven valuable not only in
benchmarking but also methods like reward modeling, constitutional AI, and self-refinement …

Scalable watermarking for identifying large language model outputs

S Dathathri, A See, S Ghaisas, PS Huang, R McAdam… - Nature, 2024 - nature.com
Large language models (LLMs) have enabled the generation of high-quality synthetic text,
often indistinguishable from human-written content, at a scale that can markedly affect the …

On protecting the data privacy of large language models (llms): A survey

B Yan, K Li, M Xu, Y Dong, Y Zhang, Z Ren… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …

Watermarks in the sand: Impossibility of strong watermarking for generative models

H Zhang, BL Edelman, D Francati, D Venturi… - arxiv preprint arxiv …, 2023 - arxiv.org
Watermarking generative models consists of planting a statistical signal (watermark) in a
model's output so that it can be later verified that the output was generated by the given …

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 …

[PDF][PDF] Reviewing the performance of AI detection tools in differentiating between AI-generated and human-written texts: A literature and integrative hybrid review

C Chaka - Journal of Applied Learning and Teaching, 2024 - researchgate.net
Since the launch of ChatGPT on 30 November 2022, much research, both academic and
non-academic papers, and numerous preprints have been published on the multiple uses …

A robust semantics-based watermark for large language model against paraphrasing

J Ren, H Xu, Y Liu, Y Cui, S Wang, D Yin… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have show great ability in various natural language tasks.
However, there are concerns that LLMs are possible to be used improperly or even illegally …

Can large language models identify authorship?

B Huang, C Chen, K Shu - arxiv preprint arxiv:2403.08213, 2024 - arxiv.org
The ability to accurately identify authorship is crucial for verifying content authenticity and
mitigating misinformation. Large Language Models (LLMs) have demonstrated an …