A position paper arguing that aleatoric/epistemic uncertainty splits fail for LLM agents and proposing underspecification, interaction, and output-based uncertainty research.
Accessed on 04.08.2024
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Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents
A position paper arguing that aleatoric/epistemic uncertainty splits fail for LLM agents and proposing underspecification, interaction, and output-based uncertainty research.