Papers by Fernando Diaz

3 papers
Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy (2025.findings-naacl)

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Challenge: Existing approaches to metric meta-evaluation focus on general statements about absolute and relative quality of metrics across arbitrary system outputs, but in practice, metrics are applied in highly contextual settings.
Approach: They propose a method for contextual metric meta-evaluation by comparing local metric accuracy.
Outcome: The proposed method compares the local metric accuracy of evaluation metrics across translation, speech recognition, and ranking tasks.
MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers (2025.emnlp-main)

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Challenge: Different retrievers offer distinct, often complementary signals, but they are not optimal for all queries.
Approach: They propose a zero-shot, weighted combination of heterogeneous retrievers . they validate this intuition by incorporating specialized non-oracle human information sources .
Outcome: Experiments show that a mixture of heterogeneous retrievers outperforms each retriever and larger models by +10.8% and +3.9% on average.
Extrinsic Evaluation of Cultural Competence in Large Language Models (2024.findings-emnlp)

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Challenge: Prior studies have evaluated models’ knowledge of cultural norms, values, and artefacts, without considering how this knowledge manifests in downstream applications.
Approach: They propose to evaluate model outputs when an explicit cue of culture, specifically nationality, is perturbed in prompts.
Outcome: The outputs of two open-ended question answering and story generation tasks are evaluated when an explicit cue of culture, specifically nationality, is perturbed in the prompts.

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