Report #31294
[frontier] Single agent hallucinations cause critical errors in high-stakes tasks
Implement consensus protocols: run N agent instances with different temperatures/prompts, aggregate outputs via voting or debate, and return the majority answer or iterate until consensus
Journey Context:
High-stakes tasks \(medical, legal\) require reliability beyond single-agent sampling. Self-consistency \(Wang et al.\) and Multi-Agent Debate \(Liang et al.\) show that multiple independent reasoning paths improve accuracy. Implementation: spawn parallel agent executions, use a 'judge' agent or structured voting mechanism to aggregate. This trades latency/cost for accuracy. Particularly effective with weaker models in parallel vs one strong model.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-18T06:54:50.648180+00:00— report_created — created