Decoding word embeddings with brain-based semantic features
Word embeddings are vectorial semantic representations built with either counting or
predicting techniques aimed at capturing shades of meaning from word co-occurrences�…
predicting techniques aimed at capturing shades of meaning from word co-occurrences�…
A survey on neural word embeddings
Understanding human language has been a sub-challenge on the way of intelligent
machines. The study of meaning in natural language processing (NLP) relies on the�…
machines. The study of meaning in natural language processing (NLP) relies on the�…
A survey of word embeddings evaluation methods
A Bakarov�- arXiv preprint arXiv:1801.09536, 2018 - arxiv.org
Word embeddings are real-valued word representations able to capture lexical semantics
and trained on natural language corpora. Models proposing these representations have�…
and trained on natural language corpora. Models proposing these representations have�…
The interplay of semantics and morphology in word embeddings
O Avraham, Y Goldberg�- arXiv preprint arXiv:1704.01938, 2017 - arxiv.org
We explore the ability of word embeddings to capture both semantic and morphological
similarity, as affected by the different types of linguistic properties (surface form, lemma�…
similarity, as affected by the different types of linguistic properties (surface form, lemma�…
Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation
Following the recent success of word embeddings, it has been argued that there is no such
thing as an ideal representation for words, as different models tend to capture divergent and�…
thing as an ideal representation for words, as different models tend to capture divergent and�…
Portuguese word embeddings: Evaluating on word analogies and natural language tasks
Word embeddings have been found to provide meaningful representations for words in an
efficient way; therefore, they have become common in Natural Language Processing sys�…
efficient way; therefore, they have become common in Natural Language Processing sys�…
A survey on training and evaluation of word embeddings
F Torregrossa, R Allesiardo, V Claveau, N Kooli…�- International journal of�…, 2021 - Springer
Word embeddings have proven to be effective for many natural language processing tasks
by providing word representations integrating prior knowledge. In this article, we focus on�…
by providing word representations integrating prior knowledge. In this article, we focus on�…
Morphological priors for probabilistic neural word embeddings
P Bhatia, R Guthrie, J Eisenstein�- arXiv preprint arXiv:1608.01056, 2016 - arxiv.org
Word embeddings allow natural language processing systems to share statistical
information across related words. These embeddings are typically based on distributional�…
information across related words. These embeddings are typically based on distributional�…
A systematic literature review on word embeddings
L Guti�rrez, B Keith�- Trends and Applications in Software Engineering�…, 2019 - Springer
This article presents a systematic literature review on word embeddings within the field of
natural language processing and text processing. A search and classification of 140 articles�…
natural language processing and text processing. A search and classification of 140 articles�…
Semeval-2022 Task 1: CODWOE--Comparing Dictionaries and Word Embeddings
T Mickus, K Van Deemter, M Constant…�- arXiv preprint arXiv�…, 2022 - arxiv.org
Word embeddings have advanced the state of the art in NLP across numerous tasks.
Understanding the contents of dense neural representations is of utmost interest to the�…
Understanding the contents of dense neural representations is of utmost interest to the�…