9 citations · 27 across the 14 of their papers we have counts for
10 papers · 1 filter
Beyond Holistic Scores: Automatic Trait-Based Quality Scoring of Argumentative Essays
Lucile Favero, Juan Antonio Pérez-Ortiz, Tanja Käser +1
Automated Essay Scoring systems have traditionally focused on holistic scores, limiting their pedagogical usefulness, especially in the case of complex essay genres such as argumen…
Multi-Hypothesis Distillation of Multilingual Neural Translation Models for Low-Resource Languages
Aarón Galiano-Jiménez, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez +1
This paper explores sequence-level knowledge distillation (KD) of multilingual pre-trained encoder-decoder translation models. We argue that the teacher model's output distribution…
ELLIS Alicante at CQs-Gen 2025: Winning the critical thinking questions shared task: LLM-based question generation and selection
Lucile Favero, Daniel Frases, Juan Antonio Pérez-Ortiz +2
The widespread adoption of chat interfaces based on Large Language Models (LLMs) raises concerns about promoting superficial learning and undermining the development of critical th…
Leveraging Small LLMs for Argument Mining in Education: Argument Component Identification, Classification, and Assessment
Lucile Favero, Juan Antonio Pérez-Ortiz, Tanja Käser +1
Argument mining algorithms analyze the argumentative structure of essays, making them a valuable tool for enhancing education by providing targeted feedback on the students' argume…
Curated Datasets and Neural Models for Machine Translation of Informal Registers between Mayan and Spanish Vernaculars
Andrés Lou, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez +1
The Mayan languages comprise a language family with an ancient history, millions of speakers, and immense cultural value, that, nevertheless, remains severely underrepresented in t…
Non-Fluent Synthetic Target-Language Data Improve Neural Machine Translation
Víctor M. Sánchez-Cartagena, Miquel Esplà-Gomis, Juan Antonio Pérez-Ortiz +1
When the amount of parallel sentences available to train a neural machine translation is scarce, a common practice is to generate new synthetic training samples from them. A number…
Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation
Víctor M. Sánchez-Cartagena, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez
This paper studies the effects of word-level linguistic annotations in under-resourced neural machine translation, for which there is incomplete evidence in the literature. The stu…
Cross-lingual neural fuzzy matching for exploiting target-language monolingual corpora in computer-aided translation
Miquel Esplà-Gomis, Víctor M. Sánchez-Cartagena, Juan Antonio Pérez-Ortiz +1
Computer-aided translation (CAT) tools based on translation memories (MT) play a prominent role in the translation workflow of professional translators. However, the reduced availa…
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
Víctor M. Sánchez-Cartagena, Miquel Esplà-Gomis, Juan Antonio Pérez-Ortiz +1
In the context of neural machine translation, data augmentation (DA) techniques may be used for generating additional training samples when the available parallel data are scarce.…
Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation
Felipe Sánchez-Martínez, Juan Antonio Pérez-Ortiz, Rafael C. Carrasco
Translation models based on hierarchical phrase-based statistical machine translation (HSMT) have shown better performances than the non-hierarchical phrase-based counterparts for…