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Found 15 papers, 4 papers with code
Unsupervised Parallel Sentence Extraction from Comparable Corpora
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.
XPASC: Measuring Generalization in Weak Supervision by Explainability and Association
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
The knowledge is captured in labeling functions, which detect certain regularities or patterns in the training samples and annotate corresponding labels for training.
UniSent: Universal Adaptable Sentiment Lexica for 1000+ Languages
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.
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly Applicable
Bilingual tasks, such as bilingual lexicon induction and cross-lingual classification, are crucial for overcoming data sparsity in the target language.
Evaluating bilingual word embeddings on the long tail
Bilingual word embeddings are useful for bilingual lexicon induction, the task of mining translations of given words.
Mapping Between English Strings and Reentrant Semantic Graphs
We investigate formalisms for capturing the relation between semantic graphs and English strings.
