Since the emergence of security concerns in artificial intelligence (AI), there has been
significant attention devoted to the examination of backdoor attacks. Attackers can utilize …

Deep learning is becoming increasingly popular in real-life applications, especially in
natural language processing (NLP). Users often choose training outsourcing or adopt third …

Large language models (LLMs) have exploded a new heatwave of AI for their ability to
engage end-users in human-level conversations with detailed and articulate answers across …

Driven by the rapid development of Large Language Models (LLMs), LLM-based agents
have been developed to handle various real-world applications, including finance …

A prompt injection attack aims to inject malicious instruction/data into the input of an LLM-
Integrated Application such that it produces results as an attacker desires. Existing works are …

Recent studies revealed that deep learning is susceptible to backdoor poisoning attacks. An
adversary can embed a hidden backdoor into a model to manipulate its predictions by only …

Large language models (LLMs) are shown to benefit from chain-of-thought (COT) prompting,
particularly when tackling tasks that require systematic reasoning processes. On the other …

Self-supervised learning in computer vision trains on unlabeled data, such as images or
(image, text) pairs, to obtain an image encoder that learns high-quality embeddings for input …

The advancement of large language models (LLMs) has significantly enhanced the ability to
effectively tackle various downstream NLP tasks and unify these tasks into generative …

Textual backdoor attacks are a kind of practical threat to NLP systems. By injecting a
backdoor in the training phase, the adversary could control model predictions via predefined …