Glossary
Consensus
In short
The points that several models agree on, which tend to be more reliable than any single model’s claims.
Ask several models the same question and the parts they all land on are usually the parts you can trust. The places they split are where the answer is genuinely uncertain or where one model went wrong.
That makes consensus useful in two directions. Agreement raises your confidence, and disagreement points you straight at the part of the task that needs a closer look.
In LLMWeave
A consensus weave surfaces what the models agree on and flags where they do not, so you are not taking one model’s word for anything that matters.
Related terms
Response synthesis
Merging several model answers into one clean result, rather than showing them side by side and making you pick.
Multi-agent debate
Having models argue different positions on a question, then settle on a conclusion, so the reasoning is tested rather than taken at face value.
Model ensemble
Combining the outputs of several models into one result, so the group performs better than any single member.
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