A conceptual framework classifies anthropomorphic deception into four levels using humanlikeness, agency, and selfhood to guide ethical and practical decisions in HCI and HRI.
Characterizing manipulation from ai systems
2 Pith papers cite this work. Polarity classification is still indexing.
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TrustLLM defines eight trustworthiness principles, creates a six-dimension benchmark, and evaluates 16 LLMs showing proprietary models generally lead but some open-source ones are close while over-calibration can hurt utility.
citing papers explorer
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Towards A Framework for Levels of Anthropomorphic Deception in Robots and AI
A conceptual framework classifies anthropomorphic deception into four levels using humanlikeness, agency, and selfhood to guide ethical and practical decisions in HCI and HRI.
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TrustLLM: Trustworthiness in Large Language Models
TrustLLM defines eight trustworthiness principles, creates a six-dimension benchmark, and evaluates 16 LLMs showing proprietary models generally lead but some open-source ones are close while over-calibration can hurt utility.