91 citations · 137 across the 3 of their papers we have counts for
8 papers
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task
Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro +9
We present the joint contribution of IST and Unbabel to the WMT 2022 Shared Task on Quality Estimation (QE). Our team participated on all three subtasks: (i) Sentence and Word-leve…
Sparse and Continuous Attention Mechanisms
André F. T. Martins, António Farinhas, Marcos Treviso +3
Exponential families are widely used in machine learning; they include many distributions in continuous and discrete domains (e.g., Gaussian, Dirichlet, Poisson, and categorical di…
The Explanation Game: Towards Prediction Explainability through Sparse Communication
Marcos V. Treviso, André F. T. Martins
Explainability is a topic of growing importance in NLP. In this work, we provide a unified perspective of explainability as a communication problem between an explainer and a laype…
Unbabel's Participation in the WMT19 Translation Quality Estimation Shared Task
Fabio Kepler, Jonay Trénous, Marcos Treviso +5
We present the contribution of the Unbabel team to the WMT 2019 Shared Task on Quality Estimation. We participated on the word, sentence, and document-level tracks, encompassing 3…
OpenKiwi: An Open Source Framework for Quality Estimation
Fábio Kepler, Jonay Trénous, Marcos Treviso +2
We introduce OpenKiwi, a PyTorch-based open source framework for translation quality estimation. OpenKiwi supports training and testing of word-level and sentence-level quality est…
Portuguese Word Embeddings: Evaluating on Word Analogies and Natural Language Tasks
Nathan Hartmann, Erick Fonseca, Christopher Shulby +3
Word embeddings have been found to provide meaningful representations for words in an efficient way; therefore, they have become common in Natural Language Processing sys- tems. In…