Using a corpus of 5542 fault-injected traces from 38 DL programs, the study finds a 0.19 balanced accuracy gap in fault diagnosis between within-program and cross-program evaluation caused by program-specific feature structures.
Ruishi Chen, Victor R Lee, Annie Camey Kuo, Denise Clark Pope, and Sarah Miles
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Causal study of 151 Java repos shows agentic AI adoption raises LOC 12.8% with unchanged total smells, producing 6.7% lower ASD as a size-driven denominator effect.
Generative AI reduced study time on AI-susceptible math problems by 9-31% across grade levels and produced a 25% decline in retention odds on proctored assessments.
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
Using distribution regression on Consumption Expenditure Interview Survey data, the study decomposes the 2018-2022 decline in consumption inequality into contributions from conditional consumption distributions, rising asset holdings, and household characteristics for male-headed households.
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Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.