Unverified50% confidenceFactExact time
When the conflict types output by the 10 decision models were used to guide generation, the frequency with which responses followed the expected behavior was comparable to using LLM-derived types.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/28/2026
First Seen
Valid until: 1/26/2027
Sources
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Related Claims
UnverifiedAcross all 11 behavioral evaluations, the SDF model expressed the implanted belief far more frequently than base Llama, including in direct questions, indirectly related tasks, adversarial system prompts, self-criticism, and four-round debates.73% similarVerifiedThe output of a decision model is often a label or probability distribution over a finite action set, similar to a policy network in reinforcement learning, whereas generative models require autoregressive sampling over a large vocabulary.70% similarVerifiedLLMs generate output token by token in an autoregressive manner, with each word's selection based on probability sampling from the current context.69% similarUnverifiedThe OWASP Top 10 for LLM Applications points out that the non-determinism of model behavior is why prompt changes need regression coverage.68% similar
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