AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The DivAlgo benchmark is proposed, a large-scale dataset constituting algorithmically diverse solutions to programming problems that is significantly less diverse than human solutions and introduces a lightweight similarity metric to enable large-scale evaluation.
Meta-evaluation of text generation metrics and LLM-judges is primarily conducted using metric-human correlations. However, prior work has shown that correlation is not an appropriate estimate of a metric's evaluation capability and can be unstable across evaluation settings, such as different datasets or languages. The...
This work presents an automated framework that classifies suspected overdoses from death investigation reports, while producing supporting explanations guided by expert knowledge, and shows that a pipeline model with explanations grounded in the input death investigation reports outperforms the other settings.
Human-centered artificial intelligence models that identify suspected overdose deaths using narrative reports from medicolegal death investigations and describe ethical considerations for using AI in overdose surveillance are developed and evaluated.
This work critically examines the effectiveness of the most common metrics used in the field, such as BLEU, embeddings, and LLMs-as-judges, and finds strong evidence that employing ensembles of diverse evaluation metrics consistently outperforms single-evaluator methods.
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