Methods, evidence and responsible applications across the AI lifecycle.
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Reliable deployment in multilingual edge cases depends on more than obtaining a strong benchmark result. This conceptual analysis uses evaluation beyond average quality to study how claims travel from data to model output and then to action...
Read article →Reliable deployment in compressed models serving multilingual outputs depends on more than obtaining a strong benchmark result. This conceptual analysis uses efficient generation to study how claims travel from data to model output and then...
Read article →Reliable deployment in multilingual services spanning devices and domains depends on more than obtaining a strong benchmark result. This conceptual analysis uses adaptive computation to study how claims travel from data to model output and...
Read article →Reliable deployment in reasoning and translation trajectories depends on more than obtaining a strong benchmark result. This conceptual analysis uses compact exploration to study how claims travel from data to model output and then to actio...
Read article →Reliable deployment in code lineages, attack histories, and forecast updates depends on more than obtaining a strong benchmark result. This conceptual analysis uses structured exploration to study how claims travel from data to model output...
Read article →This evidence synthesis examines diverse reasoning and correlated error in clinical agents that critique one another. It argues that the appropriate object of evaluation is the complete chain from incoming signal or prompt to evidence retri...
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