Analysis of bugs in modern agentic frameworks uncovers unique symptoms like unexpected execution sequences and root causes including model faults and orchestration issues, with transferable patterns across designs.
2013.Statistical power analysis for the behavioral sciences
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Sustainable scientific software projects exhibit higher and more consistent test coverage with clearer code-test correlations than unsustainable ones, while overall coverage remains low.
Input-level control over user profiles in an educational recommender system suffices to boost perceived control and positively shapes transparency, trust, satisfaction, and perceived quality, while further controls mainly reinforce impressions.
Introduces CRAI-MCF, an eight-module framework distilling 217 parameters from 240 projects into a quantitative sufficiency criterion for cross-model LLM comparison grounded in Value Sensitive Design.
citing papers explorer
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Dissecting Bug Triggers and Failure Modes in Modern Agentic Frameworks: An Empirical Study
Analysis of bugs in modern agentic frameworks uncovers unique symptoms like unexpected execution sequences and root causes including model faults and orchestration issues, with transferable patterns across designs.
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Exploring Sustainability in Scientific Software through Code Quality & Test Coverage Metrics
Sustainable scientific software projects exhibit higher and more consistent test coverage with clearer code-test correlations than unsustainable ones, while overall coverage remains low.
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Investigating the Effects of Different Levels of User Control in an Interactive Educational Recommender System
Input-level control over user profiles in an educational recommender system suffices to boost perceived control and positively shapes transparency, trust, satisfaction, and perceived quality, while further controls mainly reinforce impressions.
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Human-aligned AI Model Cards with Weighted Hierarchy Architecture
Introduces CRAI-MCF, an eight-module framework distilling 217 parameters from 240 projects into a quantitative sufficiency criterion for cross-model LLM comparison grounded in Value Sensitive Design.