5 papers
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…
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…
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…
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…
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…