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Daniel Romero-Alvarado

3 papers hereh-index 28 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG3

identity via Semantic Scholar / OpenAlex

collaborators

3 papers

cs.LG2026

Capabilities Ain't All You Need: Measuring Propensities in AI

Daniel Romero-Alvarado, Fernando Martínez-Plumed, Lorenzo Pacchiardi +11

AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired from Item Response Theory (IRT) being increasingly applied. Yet propensities - the te…

cs.LG2026

From Human-Level AI Tales to AI Leveling Human Scales

Peter Romero, Fernando Martínez-Plumed, Zachary R. Tidler +11

Comparing AI models to "human level" is often misleading when benchmark scores are incommensurate or human baselines are drawn from a narrow population. To address this, we propose…

cs.LG2025

What should an AI assessor optimise for?

Daniel Romero-Alvarado, Fernando Martínez-Plumed, José Hernández-Orallo

An AI assessor is an external, ideally indepen-dent system that predicts an indicator, e.g., a loss value, of another AI system. Assessors can lever-age information from the test r…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.