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Sixteen models, fewer than two voices: measuring ensemble dispersion where no answer is uniquely correct
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Research shows ensembling 16 LLMs from 10 families yields only 1.69 distinct semantic perspectives, revealing high redundancy in multi-model architectures.
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- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 21 September 2026
- Collected by OneBench
- 4 Aug 2026, 13:23 UK
Stored source excerpt
arXiv:2608.00285v1 Announce Type: new Abstract: Sixteen language models drawn from ten families produced, on average, the semantic diversity of 1.69 distinct formulations of a psychotherapeutic…
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