Papers by Federico Errica

1 papers
What Did I Do Wrong? Quantifying LLMs’ Sensitivity and Consistency to Prompt Engineering (2025.naacl-long)

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Challenge: Large Language Models (LLMs) have significantly improved productivity in a number of routine tasks.
Approach: They propose two metrics for classification tasks, namely *sensitivity* and *consistency*, which are complementary to task performance.
Outcome: The proposed metrics are complementary to task performance and can be used to guide prompt engineering and obtain LLMs that balance robustness and performance.

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