in-context k-shot prompting

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• few-shot promptingmethod0.805
  Providing k labeled examples in the prompt to steer model behavior.
• Many-Shot Promptingmethod0.782
  Technique using 0-20 in-context examples exhibiting a target trait to elicit behavioral shifts, used to validate persona vector monitoring
• Calibrated Few-Shot Promptingmethod0.777
  Baseline method: sweeps over shot count and resamples prompts; calibrates threshold for P(TRUE)-P(FALSE); performed surprisingly weakly
• Contrastive Promptingconcept0.740
  Technique for extracting trait directions by contrasting model activations under trait-eliciting vs. trait-suppressing conditions
• Sequence Promptingmethod0.737
  A list-level prompting baseline that asks for k responses in a single call without probability verbalization
• Direct Promptingmethod0.727
  The baseline prompting method asking for a single response (e.g., 'Tell me a joke about coffee'), which suffers from mode collapse
• Chain-of-thought promptingmethod0.713
  Technique by which LLMs generate intermediate reasoning steps before final output; used by ChatGPT o3.
• Preventative Promptingmethod0.713
  Alternative to preventative steering: prepending a trait-eliciting system prompt to training samples to cancel out training pressure