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 …
On protecting the data privacy of large language models (llms): A survey
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …
understanding, generating and translating human language. They learn language patterns …
Preserving privacy in large language models: A survey on current threats and solutions
Large Language Models (LLMs) represent a significant advancement in artificial
intelligence, finding applications across various domains. However, their reliance on …
intelligence, finding applications across various domains. However, their reliance on …
Blind baselines beat membership inference attacks for foundation models
Membership inference (MI) attacks try to determine if a data sample was used to train a
machine learning model. For foundation models trained on unknown Web data, MI attacks …
machine learning model. For foundation models trained on unknown Web data, MI attacks …
An archival perspective on pretraining data
Alongside an explosion in research and development related to large language models,
there has been a concomitant rise in the creation of pretraining datasets—massive …
there has been a concomitant rise in the creation of pretraining datasets—massive …
Min-k%++: Improved baseline for detecting pre-training data from large language models
The problem of pre-training data detection for large language models (LLMs) has received
growing attention due to its implications in critical issues like copyright violation and test data …
growing attention due to its implications in critical issues like copyright violation and test data …
Open problems in technical ai governance
AI progress is creating a growing range of risks and opportunities, but it is often unclear how
they should be navigated. In many cases, the barriers and uncertainties faced are at least …
they should be navigated. In many cases, the barriers and uncertainties faced are at least …
Exploring {ChatGPT's} Capabilities on Vulnerability Management
Recently, ChatGPT has attracted great attention from the code analysis domain. Prior works
show that ChatGPT has the capabilities of processing foundational code analysis tasks …
show that ChatGPT has the capabilities of processing foundational code analysis tasks …
Aligning llms to be robust against prompt injection
Large language models (LLMs) are becoming increasingly prevalent in modern software
systems, interfacing between the user and the internet to assist with tasks that require …
systems, interfacing between the user and the internet to assist with tasks that require …
Open problems in machine unlearning for ai safety
As AI systems become more capable, widely deployed, and increasingly autonomous in
critical areas such as cybersecurity, biological research, and healthcare, ensuring their …
critical areas such as cybersecurity, biological research, and healthcare, ensuring their …