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In this paper we describe a novel data structure for phrase-based statistical ma- chine translation which allows for the re- trieval of arbitrarily long phrases while si- multaneously using less …...

This paper describes LIMSI’s submission to the first medical translation task at WMT’14. We report results for English- French on the subtask of sentence trans- lation from summaries of medical …...

AbstractThe best solution of structured prediction models in NLP is often inaccurate because of limited expressive power of the model or to non-exact parameter estimation. One way to mitigate this …...

AbstractThis paper describes the winning system in the End-to-end Pipeline phase for the NLPContributionGraph task. The system is composed of three BERT-based models and the three models are used to …...

AbstractBack-translation is a well established approach to improve the performance of Neural Machine Translation (NMT) systems when large monolingual corpora of the target language and domain are available. Recently, diverse …...

AbstractSampling is a promising bottom-up method for exposing what generative models have learned about language, but it remains unclear how to generate representative samples from popular masked language models (MLMs) …...

AbstractMany natural language processing (NLP) tasks are naturally imbalanced, as some target categories occur much more frequently than others in the real world. In such scenarios, current NLP models tend …...

AbstractGiven a language model (LM), maximum probability is a poor decoding objective for open-ended generation, because it produces short and repetitive text. On the other hand, sampling can often produce …...

AbstractSearching troves of videos with textual descriptions is a core multimodal retrieval task. Owing to the lack of a purpose-built dataset for text-to-video retrieval, video captioning datasets have been re-purposed …...