Search Results for author: Fabienne Braune

Found 15 papers, 4 papers with code

Unsupervised Parallel Sentence Extraction from Comparable Corpora

no code implementations IWSLT (EMNLP) 2018 Viktor Hangya, Fabienne Braune, Yuliya Kalasouskaya, Alexander Fraser

We show that our approach is effective, on three language-pairs, without the use of any bilingual signal which is important because parallel sentence mining is most useful in low resource scenarios.

Sentence Word Embeddings

XPASC: Measuring Generalization in Weak Supervision by Explainability and Association

1 code implementation3 Jun 2022 Luisa März, Ehsaneddin Asgari, Fabienne Braune, Franziska Zimmermann, Benjamin Roth

To verify this assumption, we introduce a novel method, XPASC (eXPlainability-Association SCore), for measuring the generalization of a model trained with a weakly supervised dataset.

KnowMAN: Weakly Supervised Multinomial Adversarial Networks

1 code implementation EMNLP 2021 Luisa März, Ehsaneddin Asgari, Fabienne Braune, Franziska Zimmermann, Benjamin Roth

The knowledge is captured in labeling functions, which detect certain regularities or patterns in the training samples and annotate corresponding labels for training.

Language Modelling Weakly-supervised Learning

UniSent: Universal Adaptable Sentiment Lexica for 1000+ Languages

no code implementations LREC 2020 Ehsaneddin Asgari, Fabienne Braune, Benjamin Roth, Christoph Ringlstetter, Mohammad R. K. Mofrad

We introduce a method called DomDrift to mitigate the huge domain mismatch between Bible and Twitter by a confidence weighting scheme that uses domain-specific embeddings to compare the nearest neighbors for a candidate sentiment word in the source (Bible) and target (Twitter) domain.

Sentiment Analysis Unsupervised Domain Adaptation

Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly Applicable

1 code implementation ACL 2018 Viktor Hangya, Fabienne Braune, Alex Fraser, er, Hinrich Sch{\"u}tze

Bilingual tasks, such as bilingual lexicon induction and cross-lingual classification, are crucial for overcoming data sparsity in the target language.

Bilingual Lexicon Induction Classification +7

Evaluating bilingual word embeddings on the long tail

1 code implementation NAACL 2018 Fabienne Braune, Viktor Hangya, Tobias Eder, Alex Fraser, er

Bilingual word embeddings are useful for bilingual lexicon induction, the task of mining translations of given words.

Bilingual Lexicon Induction Word Embeddings

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