activity
20232026
most citedMedExpQA: Multilingual Benchmarking of Large Language Models for Medical Question Answering

50 citations · 51 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education

Rodrigo Agerri, Itziar Aldabe, Elena Cabrio +10

The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs) with educational technology.…

cs.CL2026

Explicit Evidence Grounding via Structured Inline Citation Generation

Anar Yeginbergen, Amelie Wührl, Anna Rogers +1

As AI systems become more widely adopted, the demand for factual and faithful generation grows. Properly attributing information through citations becomes, therefore, crucial. This…

cs.CL2026

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering

Anar Yeginbergen, Maite Oronoz, Rodrigo Agerri

This paper investigates Multilingual Medical Question Answering across high-resource (English, Spanish, French, Italian) and low-resource (Basque, Kazakh) languages. We evaluate th…

cs.CL2025

Lemma Dilemma: On Lemma Generation Without Domain- or Language-Specific Training Data

Olia Toporkov, Alan Akbik, Rodrigo Agerri

Lemmatization is the task of transforming all words in a given text to their dictionary forms. While large language models (LLMs) have demonstrated their ability to achieve competi…

cs.CL2025

Dynamic Knowledge Integration for Evidence-Driven Counter-Argument Generation with Large Language Models

Anar Yeginbergen, Maite Oronoz, Rodrigo Agerri

This paper investigates the role of dynamic external knowledge integration in improving counter-argument generation using Large Language Models (LLMs). While LLMs have shown promis…

cs.CL2024

CasiMedicos-Arg: A Medical Question Answering Dataset Annotated with Explanatory Argumentative Structures

Ekaterina Sviridova, Anar Yeginbergen, Ainara Estarrona +3

Explaining Artificial Intelligence (AI) decisions is a major challenge nowadays in AI, in particular when applied to sensitive scenarios like medicine and law. However, the need to…

cs.CL2024

Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniques

Anar Yeginbergen, Maite Oronoz, Rodrigo Agerri

Recent research on sequence labelling has been exploring different strategies to mitigate the lack of manually annotated data for the large majority of the world languages. Among o…

cs.CL2024★ 50 cited

MedExpQA: Multilingual Benchmarking of Large Language Models for Medical Question Answering

Iñigo Alonso, Maite Oronoz, Rodrigo Agerri

Large Language Models (LLMs) have the potential of facilitating the development of Artificial Intelligence technology to assist medical experts for interactive decision support, wh…

cs.CL2023★ 1 cited

Explanatory Argument Extraction of Correct Answers in Resident Medical Exams

Iakes Goenaga, Aitziber Atutxa, Koldo Gojenola +2

Developing the required technology to assist medical experts in their everyday activities is currently a hot topic in the Artificial Intelligence research field. Thus, a number of…