RESEARCHMonitorWATCHLIST
Multi-agent discussion gains less when dissent is withheld
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
An arXiv study models multi-agent LLM systems, showing accuracy drops when agents withhold dissent and form false consensus.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 1 October 2026
- Collected by OneBench
- 2 Oct 2026, 03:01 UK
- Original headline
- Multi-agent discussion gains less when dissent is withheld ↗
Stored source excerpt
arXiv:2609.38324v1 Announce Type: cross Abstract: Multi-agent systems of LLMs add discussion to majority voting and are therefore expected to be more capable. However, empirical reports…
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