Different elicitation discourse types surface qualitatively distinct facets of the same underlying persona

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

• Elicitation Discourse Typeconcept0.820
  Different text formats (Description, Dialogue, Narration) used to elicit persona behavior for vector extraction
• All three discourse types (Description, Dialogue, Narration) yield significant cross-steering of evil personafinding0.797
  Shows each extracted direction generalizes to evaluation prompts from other discourse types
• The model is able to express many subforms of a persona, with different elicitation methods eliciting different manifestationshypothesis0.779
  PSM-derived hypothesis supported by discourse-type facet analysis
• The phenomenological texture of a conversation is distinct from its content and worth studying.claim0.751
• Dialogue Elicitationmethod0.736
  Alternative elicitation using two-turn everyday conversations with a recurring character for persona extraction
• Stimulus-Elicited Intentionconcept0.734
  Zaadnoordijk and Bayne's category of intentional action; sticker-removal behavior induced by the self-prior corresponds to this
• A single direction encoding whether the model represents a claim as true or false is persona-relative across conversations (Lampinen et al. 2026)finding0.733
  Additional evidence that core representations are persona-relative, supporting Claim about persona-relative representations
• Chen et al. 2025 identified seven persona vectors in Qwen2.5-7B-Instruct and Llama-3.1-8B-Instruct: evil, sycophancy, hallucination, optimism, impoliteness, apathy, and humorfinding0.729
  Systematic identification of multiple coexisting persona vectors in two open-source models