Given a language model M and a statement s, does M believe s to be true?

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• Zhu et al. 2024 - Language models represent beliefs of self and othersconcept0.821
  Key prior finding that LLMs can internally represent beliefs of self and others, motivating SOO approach
• With unrestricted vocabulary, models occasionally respond in non-English Yes/No equivalents (e.g., Sí, Nein) after truth-direction interventionsfinding0.793
  Suggestive evidence for language-independent truth representation in LLMs
• We hypothesize that explicitly instructing the model to evaluate the correctness of the given statement may change the geometry of truth directions.hypothesis0.791
  Motivating hypothesis for Section 5's investigation of prompt template effects.
• Language models are few-shot learners (Brown et al., 2020)concept0.785
  Demonstrated transformers on mathematical understanding and logic; cited to motivate transformer versatility.
• All models exhibit above-baseline representation of the think word when instructed to think about itfinding0.780
  In the intentional control experiment, all tested models show above-zero cosine similarity to the think word's concept vector.
• What if the concept being manipulated does not lie on a straight line in the model's representations?question0.780
  The motivating question that opens the paper and leads to the development of manifold steering.
• a model becomes strongly confident in its final answer, but continues generating tokens without revealing its internal beliefquote0.779
  Core definitional quote for performative chain-of-thought
• Inference-Time Intervention: Eliciting Truthful Answers from a Language Model (Li et al., 2023)concept0.778
  Safety intervention that relies on activation modification, which ESR might undermine