[PDF] Top 20 Cross lingual Distillation for Text Classification
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Cross lingual Distillation for Text Classification
... Existing methods in CLTC use either a bilingual dictionary or a parallel corpus to bridge language barriers and to translate classification models (Xu et al., 2016) or text data(Zhou et al., 2016a). There ... See full document
11
A Robust Self Learning Framework for Cross Lingual Text Classification
... Sentiment Classification. To eval- uate the robustness of our framework on cross- lingual sentiment classification, we consider sev- eral diverse baselines as listed in Table ...for ... See full document
5
Attention based LSTM Network for Cross Lingual Sentiment Classification
... For the traditional LSTM network, each word in the input document is treated with equal importance, which is reasonable for traditional text classification tasks. In this paper, we propose a hierarchical ... See full document
10
Cross Lingual Classification of Topics in Political Texts
... and cross-lingual ...the cross- lingual setting (Cross-L), we train the models on the union of training instances of all four ...the Cross-L training set is four times larger ... See full document
5
Cross-lingual sentiment classification using semi-supervised learning
... Sentiment classification dates back to the early ...sentiment classification as a supervised classification problem (Pang et ...for text representation in sentiment classification (Pang ... See full document
53
Is Machine Translation Ripe for Cross Lingual Sentiment Classification?
... We use the Amazon review dataset of Pretten- hofer (2010) 1 , due to its wide range of languages (English [EN], Japanese [JP], French [FR], Ger- man [DE]) and markets (music, DVD, books). Un- like Prettenhofer (2010), we ... See full document
5
Cross Lingual Sentiment Classification with Bilingual Document Representation Learning
... Cross-lingual sentiment classification aims to adapt the sentiment resource in a resource-rich language to a resource-poor language. In this study, we propose a representation learning approach which ... See full document
10
Exploring Distributional Representations and Machine Translation for Aspect based Cross lingual Sentiment Classification
... Sentiment analysis (SA) seeks to define the underlying sentiment of a text. The best results in SA require the use of a large number of resources; from tokenizers and parsers to large sentiment lexicons or hand- ... See full document
11
Aspect Level Cross lingual Sentiment Classification with Constrained SMT
... Thus the text in the target language segment comes only from the corresponding source language seg- ment. We use the Moses statistical MT (SMT) toolkit (Koehn et al., 2007) to perform the trans- lation. In Moses, ... See full document
7
Cross Lingual Genre Classification
... Many types of features have been used in genre classification. They all fall into one of three groups: Language-specific features are cues which can only be extracted from texts in one lan- guage. An example would ... See full document
11
Multilingual Seq2seq Training with Similarity Loss for Cross Lingual Document Classification
... on text need to support these ...of text that is joint across all languages, which allows for cross-lingual transfer on the lan- guages without labeled ... See full document
5
Co Training for Cross Lingual Sentiment Classification
... subjectivity classification in Romanian (Mihalcea et ...for cross- lingual sentiment classification of Chinese prod- uct reviews by developing novel ...2.2 Cross-Domain Text ... See full document
9
Cross lingual Discourse Relation Analysis: A corpus study and a semi supervised classification system
... news text and have developed methods for the identification of discourse relations and their arguments (Wellner and Pustejovsky, 2007; Pitler et ...assessing text coherence and text quality (Pitler ... See full document
11
Semi Supervised Representation Learning for Cross Lingual Text Classification
... sentiment classification dataset 1 provided by Prettenhofer and Stein (2010), which contains Amazon product reviews in four dif- ferent languages, English (E), French (F), German (G) and Japanese ...previous ... See full document
11
Weakly Supervised Cross lingual Semantic Relation Classification via Knowledge Distillation
... for cross-lingual transfer consists of seed- ing a vanilla L EX NET model with bilingual em- beddings in the source and target languages before ...the cross-lingual paths defined ...on ... See full document
12
Cross lingual Text Classification Using Topic Dependent Word Probabilities
... Cross-lingual text classification is a major challenge in natural language processing, since often training data is available in only one language (target language), but not avail- able for ... See full document
6
Lexical and Semantic Features for Cross lingual Text Reuse Classification: an Experiment in English and Latin Paraphrases
... reused text from the ...the text inside “<ti- tle></title>” and “<description></description ...a text snippet as “text1” and to its reuse as ... See full document
5
Cross lingual intent classification in a low resource industrial setting
... various (monolingual) NLP tasks including intent classification (Kim et al., 2016). Multilingual rep- resentations of characters, words or documents can be used to solve multilingual NLP tasks. (Kle- mentiev et ... See full document
6
Bleaching Text: Abstract Features for Cross lingual Gender Prediction
... and cross-language ...gender cross-lingually, they are likely to rely on aspects beyond lexical ...the cross-language experiments, we bal- ance gender in all datasets by downsampling to the minority ... See full document
7
Combining Discourse Markers and Cross lingual Embeddings for Synonym–Antonym Classification
... Beyond classification, another di- rection for future work is to extend our approach to distinguish synonyms and antonyms from unre- lated word ...relation classification in an under- resourced language, ... See full document
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