Model merging is an efficient empowerment technique in the machine learning community
that does not require the collection of raw training data and does not require expensive …

Artificial Intelligence (AI) has steadily improved across a wide range of tasks. However, the
development and deployment of AI are almost entirely controlled by a few powerful …

As the cost of training large language models (LLMs) rises, protecting their intellectual
property has become increasingly critical. Model merging, which integrates multiple expert …

Abstract Large Language Models (LLMs) have become integral in advancing content
understanding and generation, leading to the proliferation of Embedding as a Service …

Model merging is a technique that combines multiple large pretrained models into a single
model with enhanced performance and broader task adaptability. It has gained popularity in …

Model merging has gained significant attention as a cost-effective approach to integrate
multiple single-task fine-tuned models into a unified one that can perform well on multiple …