Evolution of semantic similarity—a survey
D Chandrasekaran, V Mago - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Estimating the semantic similarity between text data is one of the challenging and open
research problems in the field of Natural Language Processing (NLP). The versatility of …
research problems in the field of Natural Language Processing (NLP). The versatility of …
Analysis methods in neural language processing: A survey
Y Belinkov, J Glass - … of the Association for Computational Linguistics, 2019 - direct.mit.edu
The field of natural language processing has seen impressive progress in recent years, with
neural network models replacing many of the traditional systems. A plethora of new models …
neural network models replacing many of the traditional systems. A plethora of new models …
Evaluating word embedding models: Methods and experimental results
Extensive evaluation on a large number of word embedding models for language
processing applications is conducted in this work. First, we introduce popular word …
processing applications is conducted in this work. First, we introduce popular word …
A survey of cross-lingual word embedding models
Cross-lingual representations of words enable us to reason about word meaning in
multilingual contexts and are a key facilitator of cross-lingual transfer when developing …
multilingual contexts and are a key facilitator of cross-lingual transfer when developing …
Interpreting pretrained contextualized representations via reductions to static embeddings
R Bommasani, K Davis, C Cardie - … of the 58th Annual Meeting of …, 2020 - aclanthology.org
Contextualized representations (eg ELMo, BERT) have become the default pretrained
representations for downstream NLP applications. In some settings, this transition has …
representations for downstream NLP applications. In some settings, this transition has …
On the limitations of unsupervised bilingual dictionary induction
Unsupervised machine translation---ie, not assuming any cross-lingual supervision signal,
whether a dictionary, translations, or comparable corpora---seems impossible, but …
whether a dictionary, translations, or comparable corpora---seems impossible, but …
All-but-the-top: Simple and effective postprocessing for word representations
Real-valued word representations have transformed NLP applications; popular examples
are word2vec and GloVe, recognized for their ability to capture linguistic regularities. In this …
are word2vec and GloVe, recognized for their ability to capture linguistic regularities. In this …
All bark and no bite: Rogue dimensions in transformer language models obscure representational quality
W Timkey, M Van Schijndel - arXiv preprint arXiv:2109.04404, 2021 - arxiv.org
Similarity measures are a vital tool for understanding how language models represent and
process language. Standard representational similarity measures such as cosine similarity …
process language. Standard representational similarity measures such as cosine similarity …
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 …
Distributional models of word meaning
A Lenci - Annual review of Linguistics, 2018 - annualreviews.org
Distributional semantics is a usage-based model of meaning, based on the assumption that
the statistical distribution of linguistic items in context plays a key role in characterizing their …
the statistical distribution of linguistic items in context plays a key role in characterizing their …