Kaipeng Zhang

Towards Unified and Effective Domain Generalization

2023 · arXiv (Cornell University)

We propose $\textbf{UniDG}$, a novel and $\textbf{Uni}$fied framework for $\textbf{D}$omain $\textbf{G}$eneralization that is capable of significantly enhancing the out-of-distribution generalization performance of foundation models regardless of their architectures. The core idea of UniDG is to …

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models

2025 · arXiv (Cornell University)

Recent advancements have shown that the Mixture of Experts (MoE) approach significantly enhances the capacity of large language models (LLMs) and improves performance on downstream tasks. Building on these promising results, multi-modal large language models …