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Lora Aroyo

Lora Aroyo has 2 papers in our library, in 2015–2023, most of them on Text generation; often with Dipanjan Das, Hannah Rashkin, Iulia Turc.

2 papers in our library · 2015–2023

current affiliationGoogle, Mountain View, United States

OpenAlex · ORCID · h-index 40 · 349 works · 7 822 citations OpenAlex, 2026-10-14

2 works in our library · 4 296 citations in our library · 1 more work in our library · ⭐ Paper Star rank #2739

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

Affiliations

🏢GoogleMountain View · United States2013–2026 · 37 paperscurrentemployment from 2018 (Wikidata)🎓Vrije Universiteit AmsterdamAmsterdam · Netherlands2006–2021 · 129 papersemployment (Wikidata)🎓Eindhoven University of TechnologyEindhoven · Netherlands2002–2011 · 63 paperseducation (Wikidata)🎓University of TwenteEnschede · Netherlands1999–2004 · 12 paperseducation until 2001 (Wikidata)🎓University of AmsterdamAmsterdam · Netherlands2009–2011 · 3 papers🏢Google DeepMindLondon · United Kingdom2025 · 2 papers🎓Leiden UniversityLeiden · Netherlands2018 · 2 papers🔬Centrum Wiskunde & InformaticaAmsterdam · Netherlands2007–2009 · 2 papers🎓Sofia University "St. Kliment Ohridski"Sofia · Bulgaria1996education until 1996 (Wikidata)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 more institutions on single bylines are not listed.

Topics

Text generation1

Works by year

2020s

20231 paper

2010s

20151 paper

Papers

The most cited first (OpenAlex and our library).

  1. Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation (2015 · 385 citations)
    Gold standards for training and testing semantic interpretation systems usually assume that each example has exactly one correct label, and they use interannotator agreement as the main quality check.
  2. Measuring Attribution in Natural Language Generation Models (2023 · 198 citations)
    Neural text generators often produce fluent statements that their underlying sources do not support. Prior work on hallucination and faithfulness lacked a shared, formally grounded way to measure this. The authors propose Attributable to Identified Sources (AIS), a framework that judges whether generated text about…

Also in our library

1 more work of theirs is in our library without a page here yet; it will appear as we publish them.

Co-authors here

7 co-authors with a page, the most papers together first.

Cited by

Papers of our library cite their works 4 296 times (of the 140 884 papers whose bibliographies we read); 302 citing papers with a page here →.

This page in Markdown → https://md.research.elamur.ai/free/en/authors/lora-aroyo/