17 citations · 37 across the 8 of their papers we have counts for
8 papers
Constraints on Dynamical Dark Energy from Multiple Probes in the Full Dark Energy Survey
DES Collaboration, T. M. C. Abbott, M. Adamow +166
We present results on dark energy evolution, assuming a time-dependent equation of state , from growth and geometric probes using the full six-year Dark Energy S…
NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark
Oscar Sainz, Jon Ander Campos, Iker García-Ferrero +3
In this position paper, we argue that the classical evaluation on Natural Language Processing (NLP) tasks using annotated benchmarks is in trouble. The worst kind of data contamina…
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models
Iker García-Ferrero, Begoña Altuna, Javier Álvez +2
Although large language models (LLMs) have apparently acquired a certain level of grammatical knowledge and the ability to make generalizations, they fail to interpret negation, a…
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri +3
Large Language Models (LLMs) combined with instruction tuning have made significant progress when generalizing to unseen tasks. However, they have been less successful in Informati…
HiTZ@Antidote: Argumentation-driven Explainable Artificial Intelligence for Digital Medicine
Rodrigo Agerri, Iñigo Alonso, Aitziber Atutxa +9
Providing high quality explanations for AI predictions based on machine learning is a challenging and complex task. To work well it requires, among other factors: selecting a prope…
IXA/Cogcomp at SemEval-2023 Task 2: Context-enriched Multilingual Named Entity Recognition using Knowledge Bases
Iker García-Ferrero, Jon Ander Campos, Oscar Sainz +2
Named Entity Recognition (NER) is a core natural language processing task in which pre-trained language models have shown remarkable performance. However, standard benchmarks like…
T-Projection: High Quality Annotation Projection for Sequence Labeling Tasks
Iker García-Ferrero, Rodrigo Agerri, German Rigau
In the absence of readily available labeled data for a given sequence labeling task and language, annotation projection has been proposed as one of the possible strategies to autom…
Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings
Iker García-Ferrero, Rodrigo Agerri, German Rigau
Zero-resource cross-lingual transfer approaches aim to apply supervised models from a source language to unlabelled target languages. In this paper we perform an in-depth study of…