How can we systematically identify effective reflection trigger instructions, rather than relying on trial-and-error?

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• Do effective trigger instructions correspond to latent directions in the hidden space that implicitly induce the self-reflection process?question0.817
  Second key research question motivating the latent direction analysis.
• Reflection is not merely a behavioral artifact of prompting but a phenomenon encoded in the model's activation space.claim0.766
  Central interpretive claim of the paper, supported by steering vector experiments.
• Some failures may reflect prompt design rather than model limitations, but the underlying issue is one of reasoning rather than instruction-following.claim0.751
  Acknowledges the confound of not explicitly instructing models to track wealth, yet points to reasoning gaps given code agents avoid errors without prompts.
• Steering vectors discover effective triggers such as 'However' and 'Otherwise', consistent with prior reported reflection datasetsfinding0.749
  Validates that steering vectors capture reflection semantics by finding tokens reported in related work.
• Enhancement steering consistently underperforms compared to directly providing explicit reflection instructions across all tested conditionsfinding0.748
  Shows that activation steering does not fully replicate mechanisms triggered by explicit prompting.
• Reflections are redundant in many cases, especially in stronger modelsclaim0.746
  Key interpretive finding that stronger models can have reflections reduced with minimal accuracy cost
• Reflection-inducing directions emerge more clearly in higher layers (ℓ>5) for both models and datasetsfinding0.734
  Empirical observation about which network layers encode reflection-relevant information.
• How do the parts discern which of their actions should be reinforced?question0.733
  Core credit assignment question for distributed systems.