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 …

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 …

Backdoor attacks have emerged as a prominent threat to natural language processing (NLP)
models, where the presence of specific triggers in the input can lead poisoned models to …

Recently, various parameter-efficient fine-tuning (PEFT) strategies for application to
language models have been proposed and successfully implemented. However, this raises …

Backdoor attacks are commonly executed by contaminating training data, such that a trigger
can activate predetermined harmful effects during the test phase. In this work, we present …

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

Federated Learning (FL), while a breakthrough in decentralized machine learning, contends
with significant challenges such as limited data availability and the variability of …

The advent of Large Language Models (LLMs) has marked significant achievements in
language processing and reasoning capabilities. Despite their advancements, LLMs face …

Pre-trained models (PTMs) are extensively utilized in various downstream tasks. Adopting
untrusted PTMs may suffer from backdoor attacks, where the adversary can compromise the …

The recent development of Foundation Models (FMs), represented by large language
models, vision transformers, and multimodal models, has been making a significant impact …