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[PDF] Top 20 Pitfalls in the Evaluation of Sentence Embeddings

Has 10000 "Pitfalls in the Evaluation of Sentence Embeddings" found on our website. Below are the top 20 most common "Pitfalls in the Evaluation of Sentence Embeddings".

Pitfalls in the Evaluation of Sentence Embeddings

Pitfalls in the Evaluation of Sentence Embeddings

... of sentence encoders has led to a large variety of proposed ...between sentence pairs (Conneau et ...learn sentence embed- dings in a multi-task setup (Subramanian et ...tence embeddings as an ... See full document

6

RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation

RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation

... This study describes a segment-level metric for automatic machine translation evaluation (MTE). The MTE metrics with a high correlation with hu- man evaluation enable the continuous integration and ... See full document

8

Simple Unsupervised Keyphrase Extraction using Sentence Embeddings

Simple Unsupervised Keyphrase Extraction using Sentence Embeddings

... EmbedRank can be implemented on top of any underlying document embeddings, provided that these embeddings can encode documents of arbi- trary length. We compared the results obtained with Doc2Vec and ... See full document

9

Scalable Cross Lingual Transfer of Neural Sentence Embeddings

Scalable Cross Lingual Transfer of Neural Sentence Embeddings

... general-purpose sentence represen- tation ...Mono-lingual evaluation of sentence representation models can be found in Hill et ...neural sentence encoders using cross-lingual natural language ... See full document

10

Learning and Evaluating Sparse Interpretable Sentence Embeddings

Learning and Evaluating Sparse Interpretable Sentence Embeddings

... word embeddings has shown that sparse representations, which can be either learned on top of existing dense embeddings or obtained through model con- straints during training time, have the bene- fit of ... See full document

11

Sentence BERT: Sentence Embeddings using Siamese BERT Networks

Sentence BERT: Sentence Embeddings using Siamese BERT Networks

... However, in the cross-topic evaluation, we ob- serve a performance drop of SBERT by about 7 points Spearman correlation. To be considered similar, arguments should address the same claims and provide the same ... See full document

11

Joint Learning of Sentence Embeddings for Relevance and Entailment

Joint Learning of Sentence Embeddings for Relevance and Entailment

... A typical approach, used implicitly in informa- tion retrieval (and its extensions, like IR-based Question Answering systems (Baudiˇs, 2015)), is to determine evidence relevancy by a keyword overlap feature (like tf-idf ... See full document

10

What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties

What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties

... linguistic evaluation of modern sentence ...capturing sentence-level proper- ties, thanks to redundancies in natural linguistic ...different embeddings, pointing out the importance of the ... See full document

11

Evaluating Sentence Compression: Pitfalls and Suggested Remedies

Evaluating Sentence Compression: Pitfalls and Suggested Remedies

... Similar to machine translation or summarization, automatic translation of paraphrastic compressions would require multiple references to capture allow- able variation, since there are often many equally valid ways of ... See full document

7

Empirical Linguistic Study of Sentence Embeddings

Empirical Linguistic Study of Sentence Embeddings

... We propose an extension and generalisation of the methodology of the probing tasks-based experi- ments. First, the current experiments are conducted on two typologically and genetically different lan- guages: English, ... See full document

11

Evaluating Word Embeddings Using a Representative Suite of Practical Tasks

Evaluating Word Embeddings Using a Representative Suite of Practical Tasks

... This evaluation aims solely to test the properties of word embeddings, and not phrase or sentence ...and sentence representations, we elect to construct these from the word embeddings ... See full document

5

Dependency Based Embeddings for Sentence Classification Tasks

Dependency Based Embeddings for Sentence Classification Tasks

... word embeddings in two word similarity datasets: WordSim-353 (Finkelstein et ...word embeddings for a pair of words to human judgements and report Spearman’s correlation in Ta- ble ...based ... See full document

11

Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts

Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts

... Recently, the work of [Treviso et al. 2017] proposed an automatic SBD method for impaired speech in Brazilian Portuguese, to allow a neuropsychological evaluation based on discourse analysis. The method uses RCNNs ... See full document

10

Verb Argument Structure Alternations in Word and Sentence Embeddings

Verb Argument Structure Alternations in Word and Sentence Embeddings

... a sentence embedding ...and sentence-level models show that some information present in word embeddings is not passed on to the down- stream sentence ... See full document

11

Encouraging Paragraph Embeddings to Remember Sentence Identity Improves Classification

Encouraging Paragraph Embeddings to Remember Sentence Identity Improves Classification

... Methods that embed a paragraph into a sin- gle vector have been successfully integrated into many NLP applications, including text classifica- tion (Zhang et al., 2017), document retrieval (Le and Mikolov, 2014), and ... See full document

8

Low Resource Corpus Filtering Using Multilingual Sentence Embeddings

Low Resource Corpus Filtering Using Multilingual Sentence Embeddings

... Zipporah (Xu and Koehn, 2017; Khayrallah et al., 2018), which is often used as a baseline comparison, uses language model and word trans- lation scores, with weights optimized to separate clean and synthetic noise data. ... See full document

6

Margin based Parallel Corpus Mining with Multilingual Sentence Embeddings

Margin based Parallel Corpus Mining with Multilingual Sentence Embeddings

... source sentence in the target side according to cosine similarity, and filtering those below a fixed ...aligned sentence pair has a larger co- sine similarity than a correctly aligned one, thus making it ... See full document

7

Learning Analogy Preserving Sentence Embeddings for Answer Selection

Learning Analogy Preserving Sentence Embeddings for Answer Selection

... Answer selection is the task of identifying the correct answer to a question from a pool of can- didate answers. The standard methodology is to prefer answers that are semantically similar to the question. Often, this ... See full document

10

Siamese CBOW: Optimizing Word Embeddings for Sentence Representations

Siamese CBOW: Optimizing Word Embeddings for Sentence Representations

... quality sentence embeddings. Averaging the embeddings of words in a sentence has proven to be a surprisingly success- ful and efficient way of obtaining sen- tence ...of sentence ... See full document

11

Summarization Based on Embedding Distributions

Summarization Based on Embedding Distributions

... In this study, we consider a summariza- tion method using the document level sim- ilarity based on embeddings, or distributed representations of words, where we as- sume that an embedding of each word can ... See full document

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