Merging methods for Large Language Models with homogeneous architecture

This table presents a structured comparison of homogeneous LLM merging approaches, where merged models share the same architecture. It summarizes key properties including baseline strategy, architecture, models used, datasets, evaluation metrics, merge space, resource requirements, and additional training dependency, providing a unified view of weight-space and training-based merging paradigms.