André F. T. Martins

research

∙ 09/21/2023

Scaling up COMETKIWI: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task

We present the joint contribution of Unbabel and Instituto Superior Técn...

0 Ricardo Rei, et al. ∙

research

∙ 08/14/2023

The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

Automatic evaluation of machine translation (MT) is a critical tool driv...

0 Patrick Fernandes, et al. ∙

research

∙ 06/09/2023

Conformalizing Machine Translation Evaluation

Several uncertainty estimation methods have been recently proposed for m...

0 Chrysoula Zerva, et al. ∙

research

∙ 05/30/2023

BLEU Meets COMET: Combining Lexical and Neural Metrics Towards Robust Machine Translation Evaluation

Although neural-based machine translation evaluation metrics, such as CO...

0 Taisiya Glushkova, et al. ∙

research

∙ 05/26/2023

CREST: A Joint Framework for Rationalization and Counterfactual Text Generation

Selective rationales and counterfactual examples have emerged as two eff...

0 Marcos Treviso, et al. ∙

research

∙ 05/20/2023

Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

The NLP community has mainly focused on scaling Large Language Models (L...

7 Ayyoob ImaniGooghari, et al. ∙

research

∙ 05/19/2023

The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics

Neural metrics for machine translation evaluation, such as COMET, exhibi...

0 Ricardo Rei, et al. ∙

research

∙ 05/01/2023

Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation

Many recent advances in natural language generation have been fueled by ...

7 Patrick Fernandes, et al. ∙

research

∙ 03/28/2023

Hallucinations in Large Multilingual Translation Models

Large-scale multilingual machine translation systems have demonstrated r...

0 Nuno M. Guerreiro, et al. ∙

research

∙ 01/18/2023

Discrete Latent Structure in Neural Networks

Many types of data from fields including natural language processing, co...

0 Vlad Niculae, et al. ∙

research

∙ 12/19/2022

Asking Clarification Questions for Code Generation in General-Purpose Programming Language

Code generation from text requires understanding the user's intent from ...

0 Haau-Sing Li, et al. ∙

research

∙ 12/19/2022

Optimal Transport for Unsupervised Hallucination Detection in Neural Machine Translation

Neural machine translation (NMT) has become the de-facto standard in rea...

0 Nuno M. Guerreiro, et al. ∙

research

∙ 10/27/2022

Improving abstractive summarization with energy-based re-ranking

Current abstractive summarization systems present important weaknesses w...

0 Diogo Pernes, et al. ∙

research

∙ 09/13/2022

CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task

We present the joint contribution of IST and Unbabel to the WMT 2022 Sha...

2 Ricardo Rei, et al. ∙

research

∙ 08/31/2022

Efficient Methods for Natural Language Processing: A Survey

Getting the most out of limited resources allows advances in natural lan...

9 Marcos Treviso, et al. ∙

research

∙ 08/10/2022

Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation

Although the problem of hallucinations in neural machine translation (NM...

0 Nuno M. Guerreiro, et al. ∙

research

∙ 05/24/2022

Chunk-based Nearest Neighbor Machine Translation

Semi-parametric models, which augment generation with retrieval, have le...

1 Pedro Henrique Martins, et al. ∙

research

∙ 05/02/2022

Quality-Aware Decoding for Neural Machine Translation

Despite the progress in machine translation quality estimation and evalu...

5 Patrick Fernandes, et al. ∙

research

∙ 04/26/2022

Efficient Machine Translation Domain Adaptation

Machine translation models struggle when translating out-of-domain text,...

1 Pedro Henrique Martins, et al. ∙

research

∙ 04/22/2022

Learning to Scaffold: Optimizing Model Explanations for Teaching

Modern machine learning models are opaque, and as a result there is a bu...

0 Patrick Fernandes, et al. ∙

research

∙ 04/13/2022

Better Uncertainty Quantification for Machine Translation Evaluation

Neural-based machine translation (MT) evaluation metrics are progressing...

0 Chrysoula Zerva, et al. ∙

research

∙ 03/04/2022

Differentiable Causal Discovery Under Latent Interventions

Recent work has shown promising results in causal discovery by leveragin...

0 Gonçalo R. A. Faria, et al. ∙

research

∙ 02/08/2022

Modeling Structure with Undirected Neural Networks

Neural networks are powerful function estimators, leading to their statu...

0 Tsvetomila Mihaylova, et al. ∙

research

∙ 09/24/2021

Predicting Attention Sparsity in Transformers

A bottleneck in transformer architectures is their quadratic complexity ...

29 Marcos Treviso, et al. ∙

research

∙ 09/13/2021

Uncertainty-Aware Machine Translation Evaluation

Several neural-based metrics have been recently proposed to evaluate mac...

0 Taisiya Glushkova, et al. ∙

research

∙ 09/09/2021

SPECTRA: Sparse Structured Text Rationalization

Selective rationalization aims to produce decisions along with rationale...

5 Nuno Miguel Guerreiro, et al. ∙

research

∙ 09/01/2021

∞-former: Infinite Memory Transformer

Transformers struggle when attending to long contexts, since the amount ...

16 Pedro Henrique Martins, et al. ∙

research

∙ 08/05/2021

Sparse Communication via Mixed Distributions

Neural networks and other machine learning models compute continuous rep...

0 António Farinhas, et al. ∙

research

∙ 08/04/2021

Sparse Continuous Distributions and Fenchel-Young Losses

Exponential families are widely used in machine learning; they include m...

0 André F. T. Martins, et al. ∙

research

∙ 05/07/2021

Measuring and Increasing Context Usage in Context-Aware Machine Translation

Recent work in neural machine translation has demonstrated both the nece...

8 Patrick Fernandes, et al. ∙

research

∙ 04/07/2021

Multimodal Continuous Visual Attention Mechanisms

Visual attention mechanisms are a key component of neural network models...

6 António Farinhas, et al. ∙

research

∙ 04/01/2021

Reconciling the Discrete-Continuous Divide: Towards a Mathematical Theory of Sparse Communication

Neural networks and other machine learning models compute continuous rep...

0 André F. T. Martins, et al. ∙

research

∙ 03/18/2021

Smoothing and Shrinking the Sparse Seq2Seq Search Space

Current sequence-to-sequence models are trained to minimize cross-entrop...

0 Ben Peters, et al. ∙

research

∙ 10/09/2020

MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset

We present MLQE-PE, a new dataset for Machine Translation (MT) Quality E...

0 Marina Fomicheva, et al. ∙

research

∙ 10/05/2020

Understanding the Mechanics of SPIGOT: Surrogate Gradients for Latent Structure Learning

Latent structure models are a powerful tool for modeling language data: ...

0 Tsvetomila Mihaylova, et al. ∙

research

∙ 07/03/2020

Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity

Training neural network models with discrete (categorical or structured)...

0 Gonçalo M. Correia, et al. ∙

research

∙ 06/12/2020

Sparse and Continuous Attention Mechanisms

Exponential families are widely used in machine learning; they include m...

0 André F. T. Martins, et al. ∙

research

∙ 04/28/2020

Towards Prediction Explainability through Sparse Communication

Explainability is a topic of growing importance in NLP. In this work, we...

0 Marcos V. Treviso, et al. ∙

research

∙ 04/06/2020

Sparse Text Generation

Current state-of-the-art text generators build on powerful language mode...

0 Pedro Henrique Martins, et al. ∙

research

∙ 01/13/2020

LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction

Structured prediction requires manipulating a large number of combinator...

0 Vlad Niculae, et al. ∙

research

∙ 08/30/2019

Adaptively Sparse Transformers

Attention mechanisms have become ubiquitous in NLP. Recent architectures...

0 Gonçalo M. Correia, et al. ∙

research

∙ 07/24/2019

Translator2Vec: Understanding and Representing Human Post-Editors

The combination of machines and humans for translation is effective, wit...

0 António Góis, et al. ∙

research

∙ 07/24/2019

Unbabel's Participation in the WMT19 Translation Quality Estimation Shared Task

We present the contribution of the Unbabel team to the WMT 2019 Shared T...

0 Fábio Kepler, et al. ∙

research

∙ 07/24/2019

Notes on Latent Structure Models and SPIGOT

These notes aim to shed light on the recently proposed structured projec...

0 André F. T. Martins, et al. ∙

research

∙ 07/18/2019

Joint Learning of Named Entity Recognition and Entity Linking

Named entity recognition (NER) and entity linking (EL) are two fundament...

0 Pedro Henrique Martins, et al. ∙

research

∙ 06/18/2019

Scheduled Sampling for Transformers

Scheduled sampling is a technique for avoiding one of the known problems...

0 Tsvetomila Mihaylova, et al. ∙

research

∙ 06/14/2019

A Simple and Effective Approach to Automatic Post-Editing with Transfer Learning

Automatic post-editing (APE) seeks to automatically refine the output of...

0 Gonçalo M. Correia, et al. ∙

research

∙ 05/30/2019

Unbabel's Submission to the WMT2019 APE Shared Task: BERT-based Encoder-Decoder for Automatic Post-Editing

This paper describes Unbabel's submission to the WMT2019 APE Shared Task...

0 António V. Lopes, et al. ∙

research

∙ 05/14/2019

Sparse Sequence-to-Sequence Models

Sequence-to-sequence models are a powerful workhorse of NLP. Most varian...

0 Ben Peters, et al. ∙

research

∙ 04/03/2019

Jointly Extracting and Compressing Documents with Summary State Representations

We present a new neural model for text summarization that first extracts...

0 Afonso Mendes, et al. ∙

André F. T. Martins

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