Novices performed better and reported lower workload with GitHub Copilot than with human partners, but human partners produced more positive emotions and a smaller drop in retest performance after one week.
Kitagawa, Monte carlo filter and smoother for non-gaussian nonlinear state space models, Journal of Computational and Graphical Statistics 5 (1) (1996) 1–25
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4verdicts
UNVERDICTED 4representative citing papers
Excessively long blocks lower asymptotic relative efficiency in the block-maxima method, and new likelihood and diagnostic procedures are proposed to check whether a chosen length is adequate under rounding or censoring.
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
Cognitive Flexibility is a new representation-level operator for Bayesian filters that dynamically selects latent structures via predictive scores to reduce inconsistency under mismatch while preserving the recursion and exhibiting descent and finite-switching properties.
citing papers explorer
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Fast and Forgettable: A Controlled Study of Novices' Performance, Learning, Workload, and Emotion in AI-Assisted and Human Pair Programming Paradigms
Novices performed better and reported lower workload with GitHub Copilot than with human partners, but human partners produced more positive emotions and a smaller drop in retest performance after one week.
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How long should a block be?
Excessively long blocks lower asymptotic relative efficiency in the block-maxima method, and new likelihood and diagnostic procedures are proposed to check whether a chosen length is adequate under rounding or censoring.
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Relationships Between Trust, Compliance, and Performance for Novice Programmers Using AI Code Generation
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
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Cognitive Flexibility as a Latent Structural Operator for Bayesian State Estimation
Cognitive Flexibility is a new representation-level operator for Bayesian filters that dynamically selects latent structures via predictive scores to reduce inconsistency under mismatch while preserving the recursion and exhibiting descent and finite-switching properties.