Learning Word Embeddings
23 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Most implemented papers
Grammatical Error Detection Using Error- and Grammaticality-Specific Word Embeddings
In this study, we improve grammatical error detection by learning word embeddings that consider grammaticality and error patterns.
MIPA: Mutual Information Based Paraphrase Acquisition via Bilingual Pivoting
We present a pointwise mutual information (PMI)-based approach to formalize paraphrasability and propose a variant of PMI, called MIPA, for the paraphrase acquisition.
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks
malllabiisc/WordGCN
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ACL 2019
Word embeddings have been widely adopted across several NLP applications.
Cross-lingual Lexical Sememe Prediction
We propose a novel framework to model correlations between sememes and multi-lingual words in low-dimensional semantic space for sememe prediction.
Poincare Glove: Hyperbolic Word Embeddings
Words are not created equal.
Learning Word Embeddings with Domain Awareness
Word embeddings are traditionally trained on a large corpus in an unsupervised setting, with no specific design for incorporating domain knowledge.
Variational Sequential Labelers for Semi-Supervised Learning
Our model family consists of a latent-variable generative model and a discriminative labeler.
Few-Shot Representation Learning for Out-Of-Vocabulary Words
acbull/HiCE
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ACL 2019
Existing approaches for learning word embeddings often assume there are sufficient occurrences for each word in the corpus, such that the representation of words can be accurately estimated from their contexts.
Towards Incremental Learning of Word Embeddings Using Context Informativeness
In this paper, we investigate the task of learning word embeddings from very sparse data in an incremental, cognitively-plausible way.
Machine Translation with Cross-lingual Word Embeddings
Learning word embeddings using distributional information is a task that has been studied by many researchers, and a lot of studies are reported in the literature.
