LLM Merging Methods in the output space

This table analyzes output-space LLM merging approaches that combine models through response-level aggregation instead of parameter manipulation. It details their fusion mechanisms, architectural constraints, training requirements, experimental setup, and baseline, clarifying the core design principles and efficiency trade-offs underlying output-level merging methods.