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Francisco Guzmán

7 accepted papers

2022

Alternative Input Signals Ease Transfer in Multilingual Machine Translation

ACL 2022long

Recent work in multilingual machine translation (MMT) has focused on the potential of positive transfer between languages, particularly cases where higher-resourced languages can benefit lower-resourced ones. While training an MMT model, the supervision signals learned from one language pair can be…

Cited by 13SourcePDFScholar
2022

OCR Improves Machine Translation for Low-Resource Languages

ACL 2022findings

We aim to investigate the performance of current OCR systems on low resource languages and low resource scripts. We introduce and make publicly available a novel benchmark, OCR4MT, consisting of real and synthetic data, enriched with noise, for 60 low-resource languages in low resource scripts. We e…

2021

Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data

ACL 2021long

The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are linguistically related or similar to high-resource languages; these related languages may share many lexical or syntactic s…

2021

Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications

EMNLP 2021main

Sentence-level Quality estimation (QE) of machine translation is traditionally formulated as a regression task, and the performance of QE models is typically measured by Pearson correlation with human labels. Recent QE models have achieved previously-unseen levels of correlation with human judgments…

Cited by 3SourcePDFScholar
2021

Improving Zero-Shot Translation by Disentangling Positional Information

ACL 2021long

Multilingual neural machine translation has shown the capability of directly translating between language pairs unseen in training, i.e. zero-shot translation. Despite being conceptually attractive, it often suffers from low output quality. The difficulty of generalizing to new translation direction…

2021

Mitigating Data Poisoning in Text Classification with Differential Privacy

EMNLP 2021finding

NLP models are vulnerable to data poisoning attacks. One type of attack can plant a backdoor in a model by injecting poisoned examples in training, causing the victim model to misclassify test instances which include a specific pattern. Although defences exist to counter these attacks, they are spec…

Cited by 10SourcePDFScholar
2021

XLEnt: Mining a Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment

EMNLP 2021main

Cross-lingual named-entity lexica are an important resource to multilingual NLP tasks such as machine translation and cross-lingual wikification. While knowledge bases contain a large number of entities in high-resource languages such as English and French, corresponding entities for lower-resource…

Cited by 14SourcePDFScholar