Uncertainty-aware dynamic steering

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• Developing uncertainty-aware dynamic steering is a promising future direction for improving reflection efficiencyclaim0.854
  Forward-looking claim connecting uncertainty-reflection hypothesis to practical future work
• Dynamic Steeringframework0.825
  Steering variants that adaptively modulate steering strength based on input context or token position, addressing when to steer
• Current steering applies fixed strength; dynamic uncertainty-aware steering during inference is an open gapquestion0.791
  Research gap identified in limitations/future work section connecting uncertainty findings to practical improvement
• Inference-Time Steeringconcept0.753
  Subtracting a scaled persona vector from hidden states at each decoding step to reduce trait expression after finetuning
• Steering vector extracted from final post-expert-iteration model also successfully elicits deployment behaviorfinding0.741
  Replicates main result using in-distribution steering vector; addresses concern about pre-trained vector validity.
• Interpretability-Driven Feedback Steeringconcept0.740
  Framework of using internal-state representations to control or steer generative models; conceptually parallel to manifold steering in language models.
• direction-based steeringconcept0.735
  Paradigm of finding the right direction in activation space (e.g., linear steering).
• Endogenous Steering Resistanceconcept0.714
  The central phenomenon introduced by this paper: inference-time recovery from irrelevant activation steering in LLMs