activity
20242026
collaborators

5 papers

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…