Challenges and applications of large language models

J Kaddour, J Harris, M Mozes, H Bradley… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

[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 …

" do anything now": Characterizing and evaluating in-the-wild jailbreak prompts on large language models

X Shen, Z Chen, M Backes, Y Shen… - Proceedings of the 2024 on …, 2024 - dl.acm.org
The misuse of large language models (LLMs) has drawn significant attention from the
general public and LLM vendors. One particular type of adversarial prompt, known as …

Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense

K Krishna, Y Song, M Karpinska… - Advances in Neural …, 2024 - proceedings.neurips.cc
The rise in malicious usage of large language models, such as fake content creation and
academic plagiarism, has motivated the development of approaches that identify AI …

Can AI-generated text be reliably detected?

VS Sadasivan, A Kumar, S Balasubramanian… - arXiv preprint arXiv …, 2023 - arxiv.org
The unregulated use of LLMs can potentially lead to malicious consequences such as
plagiarism, generating fake news, spamming, etc. Therefore, reliable detection of AI …

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 …

A survey on LLM-generated text detection: Necessity, methods, and future directions

J Wu, S Yang, R Zhan, Y Yuan, LS Chao… - Computational …, 2025 - direct.mit.edu
The remarkable ability of large language models (LLMs) to comprehend, interpret, and
generate complex language has rapidly integrated LLM-generated text into various aspects …

[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 …

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 …

Identifying and mitigating the security risks of generative ai

C Barrett, B Boyd, E Bursztein, N Carlini… - … and Trends® in …, 2023 - nowpublishers.com
Every major technical invention resurfaces the dual-use dilemma—the new technology has
the potential to be used for good as well as for harm. Generative AI (GenAI) techniques, such …