Building Semantic XOR Ensembles: Logging, Bias-Proof Judging, and Iterative Model Ratings for Multi-LLM Systems
Large-language-model (LLM) ensembles promise higher factual accuracy and richer answers than any single model, but only if the pipeline is designed to measure and mitigate bias while capturing the data needed for continuous improvement.This article describes an end-to-end pattern built around semantic XOR merging, independent judging, and rigorous logging. 1. Conceptual backdrop Element Purpose Candidate…