Extrinsic Tasks

task ID: extrinsictasks

Related Papers

Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractThe number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open …...

32716

Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractWord embeddings have been widely adopted across several NLP applications. Most existing word embedding methods utilize sequential context of a word to learn its embedding. While there have been some …...

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Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractAlthough contextualized embeddings generated from large-scale pre-trained models perform well in many tasks, traditional static embeddings (e.g., Skip-gram, Word2Vec) still play an important role in low-resource and lightweight settings due …...

37131