List of datasets in computer vision and image processing
Outline of machine learning
v
t
e
In natural language processing, a sentence embedding refers to a numeric representation of a sentence in the form of a vector of real numbers which encodes meaningful semantic information.[1][2][3][4][5][6][7][8]
State of the art embeddings are based on the learned hidden layer representation of dedicated sentence transformer models. BERT pioneered an approach involving the use of a dedicated [CLS] token prepended to the beginning of each sentence inputted into the model; the final hidden state vector of this token encodes information about the sentence and can be fine-tuned for use in sentence classification tasks. In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance[9] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.
Other approaches are loosely based on the idea of distributional semantics applied to sentences. Skip-Thought trains an encoder-decoder structure for the task of neighboring sentences predictions. Though this has been shown to achieve worse performance than approaches such as InferSent or SBERT.
An alternative direction is to aggregate word embeddings, such as those returned by Word2vec, into sentence embeddings. The most straightforward approach is to simply compute the average of word vectors, known as continuous bag-of-words (CBOW).[10] However, more elaborate solutions based on word vector quantization have also been proposed. One such approach is the vector of locally aggregated word embeddings (VLAWE),[11] which demonstrated performance improvements in downstream text classification tasks.
^Paper Summary: Evaluation of sentence embeddings in downstream and linguistic probing tasks
^Wu, Ledell; Fisch, Adam; Chopra, Sumit; Adams, Keith; Bordes, Antoine; Weston, Jason (2017). "StarSpace: Embed All the Things!". arXiv:1709.03856 [cs.CL].
^Sanjeev Arora, Yingyu Liang, and Tengyu Ma. "A simple but tough-to-beat baseline for sentence embeddings.", 2016; openreview:SyK00v5xx.
^Trifan, Mircea; Ionescu, Bogdan; Gadea, Cristian; Ionescu, Dan (2015). "A graph digital signal processing method for semantic analysis". 2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics. pp. 187–192. doi:10.1109/SACI.2015.7208196. ISBN 978-1-4799-9911-8. S2CID 17099431.
^Basile, Pierpaolo; Caputo, Annalina; Semeraro, Giovanni (2012). "A Study on Compositional Semantics of Words in Distributional Spaces". 2012 IEEE Sixth International Conference on Semantic Computing. pp. 154–161. doi:10.1109/ICSC.2012.55. ISBN 978-1-4673-4433-3. S2CID 552921.
^Mikolov, Tomas; Chen, Kai; Corrado, Greg; Dean, Jeffrey (2013-09-06). "Efficient Estimation of Word Representations in Vector Space". arXiv:1301.3781 [cs.CL].
^Ionescu, Radu Tudor; Butnaru, Andrei (2019). "Vector of Locally-Aggregated Word Embeddings (". Proceedings of the 2019 Conference of the North. Minneapolis, Minnesota: Association for Computational Linguistics. pp. 363–369. doi:10.18653/v1/N19-1033. S2CID 85500146. {{cite book}}: |journal= ignored (help)
and 25 Related for: Sentence embedding information
In natural language processing, a sentenceembedding refers to a numeric representation of a sentence in the form of a vector of real numbers which encodes...
In natural language processing (NLP), a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation...
In linguistics, center embedding is the process of embedding a phrase in the middle of another phrase of the same type. This often leads to difficulty...
embedded, embed, or embedding in Wiktionary, the free dictionary. Embedded or embedding (alternatively imbedded or imbedding) may refer to: Embedding...
thinks that...," or by combining shorter clauses. Sentences can also be extended by recursively embedding clauses one into another, such as "The mouse ran...
which preserves embedding orders [further explanation needed] via probability distributions, triplet loss works directly on embedded distances. Therefore...
cleft sentence is a complex sentence (one having a main clause and a dependent clause) that has a meaning that could be expressed by a simple sentence. Clefts...
Other key techniques in this field are negative sampling and word embedding. Word embedding, such as word2vec, can be thought of as a representational layer...
subclause or embedded clause, is a certain type of clause that juxtaposes an independent clause within a complex sentence. For instance, in the sentence "I know...
database Gensim Phraseme Random indexing Sentenceembedding Statistical semantics Word2vec Word embedding Scott Deerwester Susan Dumais J. R. Firth George...
center embedding in sentences, which involves the embedding of a clause into the middle of another clause of the same type. Although center embedding is a...
In syntax, verb-second (V2) word order is a sentence structure in which the finite verb of a sentence or a clause is placed in the clause's second position...
then M is called an elementary extension of N. An embedding h: N → M is called an elementary embedding of N into M if h(N) is an elementary substructure...
The algorithm is also used by the SpaCy library to build semantic word embedding features, while computing the top list words that match with distance...
embedded within a phrase, for example: "Paul knows who is sick", where the interrogative clause "who is sick" serves as complement of the embedding verb...
Townsend, David J.; Bever, Thomas G. (2001). "Embedding the Grammar in a Comprehension Model". Sentence Comprehension: The Integration of Habits and Rules...
A "Nominal" sentence (also known as equational sentence) is a linguistic term that refers to a nonverbal sentence (i.e. a sentence without a finite verb)...
sub-sentential expression consists in its contribution to the thought that its embeddingsentence expresses. Senses determine reference and are also the modes of presentation...
research to help scholars stay up to date. It uses a state-of-the-art paper embedding model trained using contrastive learning to find papers similar to those...
wh-clauses. The b-sentences are direct questions (independent clauses), and the c-sentences contain the corresponding indirect questions (embedded clauses): a...
this to explain some properties of word embeddings, including their use to solve analogies. The word embedding approach is able to capture multiple different...
pre-trained language models (XLM-RoBERTa, Language Agnostic BERT SentenceEmbeddings (LaBSE)) fine-tuned on the HASOC2021 dataset proposed by the organisers...
Sentence processing takes place whenever a reader or listener processes a language utterance, either in isolation or in the context of a conversation or...
Global Information