Large language models (LLMs) have emerged as important components across various
fields, yet their training requires substantial computation resources and abundant labeled …

Federated learning aims to facilitate collaborative training among multiple clients with data
heterogeneity in a privacy-preserving manner, which either generates the generalized …

The scarcity of well-annotated medical datasets requires leveraging transfer learning from
broader datasets like ImageNet or pre-trained models like CLIP. Model soups averages …

Pre-training followed by fine-tuning is widely adopted among practitioners. The performance
can be improved by" model soups"~\cite {wortsman2022model} via exploring various …

As generative dialog models become ubiquitous in real-world applications, it is paramount
to ensure a harmless generation. There are two major challenges when enforcing safety to …

Breast cancer remains a critical problem. Its complexity requires robust methods to
understand the underlying genetic interactions. This research applies a three-part approach …