It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief
Users frequently express their beliefs to large language models (LLMs). In some situations, the LLM should accept these contextual beliefs as true. In others, they should stick to their prior knowledge. Notably, users' expressions of belief (EoBs) can take linguistically diverse forms - using presuppositions, evidential and certainty markers, or varied tones - each of which may have a different persuasiveness over the LLMs. We introduce a typology to systematically evaluate how different EoBs affect whether models follow context versus prior knowledge. The typology is grounded in four linguist
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- PossiblePossibly related (embedding) · 52%Understanding large language models demands distinguishing human projection from machine cognition - Nature →
- LinkedLinked via arxiv author · 85%Kevin Du →
“It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief”
- LinkedLinked via arxiv author · 85%Clara Kümpel →
“It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief”
- LinkedLinked via arxiv author · 85%Michelle Wastl →
“It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief”
- LinkedLinked via arxiv author · 85%Alex Warstadt →
“It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief”