Diffusion models and large language models have emerged as leading-edge generative
models and have sparked a revolutionary impact on various aspects of human life. However …

As a specific category of artificial intelligence (AI), generative artificial intelligence (GenAI)
generates new content that resembles what humans create. The rapid development of …

Recent years have witnessed remarkable progress made in large language models (LLMs).
Such advancements, while garnering significant attention, have concurrently elicited various …

Federated learning allows distributed users to collaboratively train a model while keeping
each user's data private. Recently, a growing body of work has demonstrated that an …

The inevitable private information in legal data necessitates legal artificial intelligence to
study privacy-preserving and decentralized learning methods. Federated learning (FL) has …

Retrieval-based language models (LMs) have demonstrated improved interpretability,
factuality, and adaptability compared to their parametric counterparts, by incorporating …

Recent work shows that sensitive user data can be reconstructed from gradient updates,
breaking the key privacy promise of federated learning. While success was demonstrated …

Large Language Models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

To ensure AI safety, instruction-tuned Large Language Models (LLMs) are specifically
trained to ensure alignment, which refers to making models behave in accordance with …

Federated learning (FL) has emerged as a secure paradigm for collaborative training among
clients. Without data centralization, FL allows clients to share local information in a privacy …