134 citations · 232 across the 13 of their papers we have counts for
16 papers
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…
Traffic incident duration prediction via a deep learning framework for text description encoding
Artur Grigorev, Adriana-Simona Mihaita, Khaled Saleh +1
Predicting the traffic incident duration is a hard problem to solve due to the stochastic nature of incident occurrence in space and time, a lack of information at the beginning of…
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…