Word Embeddings
Eigenwords: Spectral Word Embeddings
... learning word embeddings (eigenwords) which are fast to train, have strong theoretical properties, can induce context specific embeddings and have better sample complexity for rare ...
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Evaluation of Croatian Word Embeddings
... To the best of our knowledge, only small portion of re- cent studies attempted evaluating Croatian word embed- dings. In a review of works that evaluate syntactic and se- mantic analogies, we have encountered only ...
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Evaluation of acoustic word embeddings
... acoustic word embed- ...acoustic word embeddings in comparison to ortho- graphic representations in order to eval- uate whether they capture discriminative phonetic ...
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Word Embeddings through Hellinger PCA
... We claim that, assuming an appropriate met- ric, a simple spectral method as PCA can generate word embeddings as good as with deep-learning architectures. On the other hand, deep-learning architectures have ...
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Making Sense of Word Embeddings
... with word embeddings and clustered. Second, word occurrences are re- labeled in the corpus according to the cluster they belong ...Finally, embeddings are re-trained on this sense-labeled ...
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Exploring Numeracy in Word Embeddings
... Word embeddings are now pervasive across NLP subfields as the de-facto method of form- ing text ...well word embeddings capture two es- sential properties of numbers: magnitude ...
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Geographical Evaluation of Word Embeddings
... While the mean geographic distance is a good metric for a global view, it does not take the lo- cal structure into account, i.e. a random model moves the cities in all directions and breaks the lo- cal structure (nearest ...
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Searching for the X Factor: Exploring Corpus Subjectivity for Word Embeddings
... best word em- bedding methods are shown in ...Subjective word embed- ...the word embed- dings comes from separate lexical resources, and does not involve any sentiment classification ...two ...
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Retrofitting Contextualized Word Embeddings with Paraphrases
... Contextualized word embedding models have been studied by a series of recent research ef- forts, where different types of pre-trained lan- guage models are employed to capture the context ...contextualized ...
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Learning Gender Neutral Word Embeddings
... Coreference Resolution Finally, we investigate how the gender bias in word embeddings affects a downstream application, such as coreference res- olution. Coreference resolution aims at clustering the ...
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Misspelling Oblivious Word Embeddings
... their embeddings from demonstrating any inter- esting ...every word in the corpus would on the other hand cause up to an exponential growth in the size of the train- ing data, making training of the models ...
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Querying Word Embeddings for Similarity and Relatedness
... each word has led to the suggestion that distinct representations, and perhaps even distinct learn- ing models, are needed for optimal performance on these distinct tasks (Mandera et ...as word embedding ...
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Literal or idiomatic? Identifying the reading of single occurrences of German multiword expressions using word embeddings
... work. Word embeddings seemed like a more promising way of representing the mean- ing of words since a plain co-occurence-based ap- proach like the NGD has some considerable lim- itations as we will discuss ...
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Reconstruction of Word Embeddings from Sub Word Parameters
... sub- word parameters must reproduce the topology of word embeddings which are not always morpho- logically coherent ...tasks: word similarity, word analogy, and POS ...the word ...
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Domain Adapted Word Embeddings for Improved Sentiment Classification
... monolingual word embed- dings across data sets in different application do- mains/contexts for the purpose of a given down- stream task such as sentiment ...ing word embeddings across different ...
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Multilingual Training of Crosslingual Word Embeddings
... bilingual word embeddings. Our multilingual word embeddings, on the other hand, map both Italian and Spanish to the same space without using any direct bilingual signal between ...multilingual ...
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Dependency Based Word Embeddings
... the word and a particu- lar context (see (Turney and Pantel, 2010; Baroni and Lenci, 2010) for a comprehensive ...sparse word-context vectors is reduced, using techniques such as SVD (Bullinaria and Levy, ...
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Word Embeddings with Limited Memory
... when word embeddings are being used and in ...isting word and phrase similarity and relatedness datasets as well as on dependency parsing, to e- valuate these ...truncated word ...
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Urdu Word Embeddings
... of word embeddings from large unannotated corpora has been a wa- tershed moment in natural language processing in recent ...of embeddings has not only improved the state-of-the-art in multiple ...
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Evaluating semantic relations in neural word embeddings with biomedical and general domain knowledge bases
... of word embeddings and the interpretability of the applications using them, in this study, we propose a novel approach for evaluating the semantic relations in word embeddings using external ...
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