Security and privacy challenges of large language models: A survey
Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …
contributed to multiple fields, such as generating and summarizing text, language …
Distributed artificial intelligence empowered by end-edge-cloud computing: A survey
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …
also supports artificial intelligence evolving from a centralized manner to a distributed one …
Glaze: Protecting artists from style mimicry by {Text-to-Image} models
Recent text-to-image diffusion models such as MidJourney and Stable Diffusion threaten to
displace many in the professional artist community. In particular, models can learn to mimic …
displace many in the professional artist community. In particular, models can learn to mimic …
A survey of machine unlearning
Today, computer systems hold large amounts of personal data. Yet while such an
abundance of data allows breakthroughs in artificial intelligence, and especially machine …
abundance of data allows breakthroughs in artificial intelligence, and especially machine …
Foundational challenges in assuring alignment and safety of large language models
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 …
language models (LLMs). These challenges are organized into three different categories …
A comprehensive survey on poisoning attacks and countermeasures in machine learning
The prosperity of machine learning has been accompanied by increasing attacks on the
training process. Among them, poisoning attacks have become an emerging threat during …
training process. Among them, poisoning attacks have become an emerging threat during …
Dataset distillation: A comprehensive review
Recent success of deep learning is largely attributed to the sheer amount of data used for
training deep neural networks. Despite the unprecedented success, the massive data …
training deep neural networks. Despite the unprecedented success, the massive data …
Rethinking machine unlearning for large language models
S Liu, Y Yao, J Jia, S Casper, N Baracaldo… - arxiv preprint arxiv …, 2024 - arxiv.org
We explore machine unlearning (MU) in the domain of large language models (LLMs),
referred to as LLM unlearning. This initiative aims to eliminate undesirable data influence …
referred to as LLM unlearning. This initiative aims to eliminate undesirable data influence …
A survey on ChatGPT: AI-generated contents, challenges, and solutions
With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-
generated content (AIGC) has garnered increasing attention and is leading a paradigm shift …
generated content (AIGC) has garnered increasing attention and is leading a paradigm shift …
Anti-backdoor learning: Training clean models on poisoned data
Backdoor attack has emerged as a major security threat to deep neural networks (DNNs).
While existing defense methods have demonstrated promising results on detecting or …
While existing defense methods have demonstrated promising results on detecting or …