D-Shap reformulates dynamic Shapley valuation as structured matrix maintenance exploiting utility and coalition locality to support millisecond task updates and orders-of-magnitude cheaper player updates.
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Neural networks learn to construct argumentation structures that explain classifications through support and attack relations, trained jointly with differentiable semantics and structure constraints.
Human tests should not be applied to AI to measure traits like intelligence due to calibration, validity, contamination, and prompt sensitivity issues; develop AI-specific evaluation frameworks instead.
citing papers explorer
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Dynamic Shapley Computation
D-Shap reformulates dynamic Shapley valuation as structured matrix maintenance exploiting utility and coalition locality to support millisecond task updates and orders-of-magnitude cheaper player updates.
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Deep Arguing
Neural networks learn to construct argumentation structures that explain classifications through support and attack relations, trained jointly with differentiable semantics and structure constraints.
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Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead
Human tests should not be applied to AI to measure traits like intelligence due to calibration, validity, contamination, and prompt sensitivity issues; develop AI-specific evaluation frameworks instead.