A robot's sense-making of fallacies and rhetorical tropes. Creating ontologies of what humans try to say
원문 초록
In the design of user-friendly robots, human communication should be understood by the system beyond mere logics and literal meaning. Robot communication-design has long ignored the importance of communication and politeness rules that are 'forgiving' and 'suspending disbelief' and cannot handle the basically metaphorical way humans design their utterances. Through analysis of the psychological causes of illogical and non-literal statements, signal detection, fundamental attribution errors, and anthropomorphism, we developed a fail-safe protocol for fallacies and tropes that makes use of Frege's distinction between reference and sense, Beth's tableau analytics, Grice's maxim of quality, and epistemic considerations to have the robot politely make sense of a user's sometimes unintelligible demands. Keywords: social robots, logical fallacies, metaphors, reference, sense, maxim of quality, tableau reasoning, epistemics of the virtual
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Leveraging Context for Multimodal Fallacy Classification in Political Debates
Socrates or Smartypants: Testing Logic Reasoning Capabilities of Large Language Models with Logic Programming-based Test Oracles
Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation
RuozhiBench: Evaluating LLMs with Logical Fallacies and Misleading Premises
Boosting Logical Fallacy Reasoning in LLMs via Logical Structure Tree
Grounding Fallacies Misrepresenting Scientific Publications in Evidence
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