[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 …

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 …

A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions

L Huang, W Yu, W Ma, W Zhong, Z Feng… - ACM Transactions on …, 2025 - dl.acm.org
The emergence of large language models (LLMs) has marked a significant breakthrough in
natural language processing (NLP), fueling a paradigm shift in information acquisition …

[PDF][PDF] Trustllm: Trustworthiness in large language models

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

Jailbreak and guard aligned language models with only few in-context demonstrations

Z Wei, Y Wang, A Li, Y Mo, Y Wang - arxiv preprint arxiv:2310.06387, 2023 - arxiv.org
Large Language Models (LLMs) have shown remarkable success in various tasks, yet their
safety and the risk of generating harmful content remain pressing concerns. In this paper, we …

Can llm-generated misinformation be detected?

C Chen, K Shu - arxiv preprint arxiv:2309.13788, 2023 - arxiv.org
The advent of Large Language Models (LLMs) has made a transformative impact. However,
the potential that LLMs such as ChatGPT can be exploited to generate misinformation has …

Foundational challenges in assuring alignment and safety of large language models

U Anwar, A Saparov, J Rando, D Paleka… - arxiv preprint arxiv …, 2024 - arxiv.org
This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

[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 …

Knowledge conflicts for llms: A survey

R Xu, Z Qi, Z Guo, C Wang, H Wang, Y Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
This survey provides an in-depth analysis of knowledge conflicts for large language models
(LLMs), highlighting the complex challenges they encounter when blending contextual and …