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Predicting Machine Translation Adequacy with Document Embeddings
Mihaela Vela
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Liling Tan
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Paper Details:
Month: September
Year: 2015
Location: Lisbon, Portugal
Venue:
WMT |
WS |
SIG: SIGMT
Citations
URL
Word2Vec vs DBnary: Augmenting METEOR using Vector Representations or Lexical Resources?
Christophe Servan
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Alexandre Bérard
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Zied Elloumi
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Hervé Blanchon
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Laurent Besacier
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SubCo: A Learner Translation Corpus of Human and Machine Subtitles
José Manuel Martínez Martínez
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Mihaela Vela
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WOLVESAAR at SemEval-2016 Task 1: Replicating the Success of Monolingual Word Alignment and Neural Embeddings for Semantic Textual Similarity
Hannah Bechara
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Rohit Gupta
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Liling Tan
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Constantin Orăsan
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Ruslan Mitkov
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Josef van Genabith
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Results of the WMT15 Metrics Shared Task
Miloš Stanojević
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Amir Kamran
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Philipp Koehn
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Ondřej Bojar
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An Awkward Disparity between BLEU / RIBES Scores and Human Judgements in Machine Translation
Liling Tan
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Jon Dehdari
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Josef van Genabith
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Modifications of Machine Translation Evaluation Metrics by Using Word Embeddings
Haozhou Wang
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Paola Merlo
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http://tinyurl.com/pywsd-cosine
https://github.com/alvations/warmth
Field Of Study
Linguistic Trends
Distributional Semantics
Embeddings
Syntax
Task
Semantic Similarity
Machine Translation
Language
Multilingual
English
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