Mean truthfulness is not influenced by the context score for any model in Experiment 6.

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

• The model appears to encode truth differently under passive versus active truth evaluation prompts.claim0.789
  Key finding from Section 5 based on low cosine similarity between no-prompt and ask-correct probes.
• Traits such as truthfulness and harmfulness can be stationary in certain contexts but reflective in others.claim0.788
  Central finding of Section 5 on trait dynamics in interactions.
• We hypothesize that explicitly instructing the model to evaluate the correctness of the given statement may change the geometry of truth directions.hypothesis0.772
  Motivating hypothesis for Section 5's investigation of prompt template effects.
• The model tends to reflect more when the question is difficult, and accuracy is generally lower for harder questionshypothesis0.770
  Hypothesis explaining negative correlation between reflection rate and accuracy without implying reflection is harmful
• Inference-Time Intervention: Eliciting Truthful Answers from a Language Model (Li et al., 2023)concept0.770
  Safety intervention that relies on activation modification, which ESR might undermine
• How does reflection influence the model's reasoning performance?question0.764
  Second central research question motivating ReflCtrl investigation
• Does instructing the model to assess correctness affect the geometry of truth directions?question0.760
  One of the three guiding research questions of the paper.
• How does contextual framing modulate deception tendencies across different paradigms?question0.759
  Identified limitation and future research direction in the paper's conclusions