134 citations · 144 across the 13 of their papers we have counts for
16 papers
En-ViMedNER: An English-Vietnamese Parallel Biomedical Corpus with UMLS Semantic Type Annotations
Nhu Vo, Phuong Nguyen, Nu Uyen Phuong Le +4
Biomedical Named Entity Recognition (NER) is fundamental to healthcare AI applications, including clinical decision support and medical information extraction. While corpora with U…
Pref-CTRL: Preference Driven LLM Alignment using Representation Editing
Imranul Ashrafi, Inigo Jauregi Unanue, Massimo Piccardi
Test-time alignment methods offer a promising alternative to fine-tuning by steering the outputs of large language models (LLMs) at inference time with lightweight interventions on…
ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmark
Tung X. Nguyen, Nhu Vo, Giang-Son Nguyen +6
Code-switching (CS), which is when Vietnamese speech uses English words like drug names or procedures, is a common phenomenon in Vietnamese medical communication. This creates chal…
A Constraint-Enforcing Reward for Adversarial Attacks on Text Classifiers
Tom Roth, Inigo Jauregi Unanue, Alsharif Abuadbba +1
Text classifiers are vulnerable to adversarial examples -- correctly-classified examples that are deliberately transformed to be misclassified while satisfying acceptability constr…
SumTra: A Differentiable Pipeline for Few-Shot Cross-Lingual Summarization
Jacob Parnell, Inigo Jauregi Unanue, Massimo Piccardi
Cross-lingual summarization (XLS) generates summaries in a language different from that of the input documents (e.g., English to Spanish), allowing speakers of the target language…
A Generative Adversarial Attack for Multilingual Text Classifiers
Tom Roth, Inigo Jauregi Unanue, Alsharif Abuadbba +1
Current adversarial attack algorithms, where an adversary changes a text to fool a victim model, have been repeatedly shown to be effective against text classifiers. These attacks,…
T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification
Inigo Jauregi Unanue, Gholamreza Haffari, Massimo Piccardi
Cross-lingual text classification leverages text classifiers trained in a high-resource language to perform text classification in other languages with no or minimal fine-tuning (z…
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization
Jacob Parnell, Inigo Jauregi Unanue, Massimo Piccardi
Multi-document summarization (MDS) has made significant progress in recent years, in part facilitated by the availability of new, dedicated datasets and capacious language models.…
RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation
Jacob Parnell, Inigo Jauregi Unanue, Massimo Piccardi
To date, most abstractive summarisation models have relied on variants of the negative log-likelihood (NLL) as their training objective. In some cases, reinforcement learning has b…
BERTTune: Fine-Tuning Neural Machine Translation with BERTScore
Inigo Jauregi Unanue, Jacob Parnell, Massimo Piccardi
Neural machine translation models are often biased toward the limited translation references seen during training. To amend this form of overfitting, in this paper we propose fine-…
Leveraging Discourse Rewards for Document-Level Neural Machine Translation
Inigo Jauregi Unanue, Nazanin Esmaili, Gholamreza Haffari +1
Document-level machine translation focuses on the translation of entire documents from a source to a target language. It is widely regarded as a challenging task since the translat…
Learning Neural Textual Representations for Citation Recommendation
Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham +2
With the rapid growth of the scientific literature, manually selecting appropriate citations for a paper is becoming increasingly challenging and time-consuming. While several appr…
Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
In recent years, neural machine translation (NMT) has become the dominant approach in automated translation. However, like many other deep learning approaches, NMT suffers from ove…
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Nazanin Esmaili +1
Regularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (Re…
A Shared Attention Mechanism for Interpretation of Neural Automatic Post-Editing Systems
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
Automatic post-editing (APE) systems aim to correct the systematic errors made by machine translators. In this paper, we propose a neural APE system that encodes the source (src) a…
Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
Background. Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and c…