Papers by Ander Barrena
Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction (2021.emnlp-main)
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| Challenge: | Relation extraction systems require large amounts of labeled examples which are costly to annotate. |
| Approach: | They propose to use hand-made relation extraction tasks to refine a pretrained textual entailment engine which is run as-is or further fine-tuned on labeled examples. |
| Outcome: | The proposed system achieves 63% F1 zero-shot, 69% with 16 examples per relation and 4 points short of the state-of-the-art system on the same conditions. |
Give your Text Representation Models some Love: the Case for Basque (2020.lrec-1)
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Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos, Ander Barrena, Xabier Saralegi, Aitor Soroa, Eneko Agirre
| Challenge: | Word embeddings and pre-trained language models are expensive to train and are often used by small companies and research groups to build their own. |
| Approach: | They propose to use word embeddings and pre-trained language models to build rich representations of text and improve NLP tasks. |
| Outcome: | The proposed models perform better than publicly available versions in downstream NLP tasks for Basque. |
Ranking Over Scoring: Towards Reliable and Robust Automated Evaluation of LLM-Generated Medical Explanatory Arguments (2025.coling-main)
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Iker De la Iglesia, Iakes Goenaga, Johanna Ramirez-Romero, Jose Maria Villa-Gonzalez, Josu Goikoetxea, Ander Barrena
| Challenge: | Evaluating LLM-generated text has become a key challenge in domain-specific contexts like the medical field. |
| Approach: | They propose a method to evaluate LLM-generated medical explanatory arguments using Proxy Tasks and rankings to align results with human evaluation criteria. |
| Outcome: | The proposed evaluation method is robust against adversarial attacks, including the assessment of non-argumentative text. |