Agentic self-steering evaluation

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• Agentic self-steering evaluation may serve as a general method for explaining and interpreting SAE features beyond emotionclaim0.884
  Forward-looking claim about the broader utility of the self-steering evaluation method
• If agentic self-steering evaluation proves robust, it might be used to better explain and interpret SAE features in generalhypothesis0.860
  Speculative claim about scaling introspective access to general SAE feature interpretation
• Agentic self-evaluation and self-steering may scale to broadly interpret and understand internal representations and SAE features.claim0.859
  Forward-looking claim about the potential of model introspection as an interpretability tool
• Whether the advantage of agentic self-evaluation over textual evaluation in predicting persistence is due to introspection quality or to testing of additional (including negative) steering strengthsquestion0.768
  Identified methodological gap in interpreting the self-evaluation experiment results
• agentic reasoningconcept0.758
  Reasoning approach using code or tool calls executed by an agent.
• Agentic self-evaluation emotionality correlates with SAE feature persistence: rho=+0.124, p=0.0001finding0.740
  Shows that features Kimi rates as more emotional via self-steering are more persistent, independent of probe construction
• Interpretability-Driven Feedback Steeringconcept0.739
  Framework of using internal-state representations to control or steer generative models; conceptually parallel to manifold steering in language models.
• Agentic Visual Reasoningconcept0.737
  Paradigm where VLM acts as controller generating code or tool calls to external modules for visual operations, incurring context-switching latency.