SOTAVerified

Word Similarity

Calculate a numerical score for the semantic similarity between two words.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 378 papers

TitleStatusHype
Bilingual Embeddings with Random Walks over Multilingual Wordnets—0
Bio-inspired Structure Identification in Language Embeddings—0
Bridging Natural Language Processing and Psycholinguistics: computationally grounded semantic similarity datasets for Basque and Spanish—0
Can Eye Movement Data Be Used As Ground Truth For Word Embeddings Evaluation?—0
Can Network Embedding of Distributional Thesaurus be Combined with Word Vectors for Better Representation?—0
Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Models—0
Category Enhanced Word Embedding—0
Charagram: Embedding Words and Sentences via Character n-grams—0
Chinese Embedding via Stroke and Glyph Information: A Dual-channel View—0
Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning—0
Citius at SemEval-2017 Task 2: Cross-Lingual Similarity from Comparable Corpora and Dependency-Based Contexts—0
CitiusNLP at SemEval-2020 Task 3: Comparing Two Approaches for Word Vector Contextualization—0
Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research—0
Community Detection in Political Twitter Networks using Nonnegative Matrix Factorization Methods—0
Comparing in context: Improving cosine similarity measures with a metric tensor—0
Comparison between the Structures of Word Co-occurrence and Word Similarity Networks for Ill-formed and Well-formed Texts in Taiwan Mandarin—0
Component-Enhanced Chinese Character Embeddings—0
Confusion2Vec: Towards Enriching Vector Space Word Representations with Representational Ambiguities—0
Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings—0
Constructing a Word Similarity Graph from Vector based Word Representation for Named Entity Recognition—0
Correlation-based Intrinsic Evaluation of Word Vector Representations—0
Creation and Evaluation of Datasets for Distributional Semantics Tasks in the Digital Humanities Domain—0
Cross-lingual Semantic Specialization via Lexical Relation Induction—0
Cross-Lingual Syntactically Informed Distributed Word Representations—0
Cross-topic distributional semantic representations via unsupervised mappings—0
Deep Multilingual Correlation for Improved Word Embeddings—0
Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings—0
Dirichlet-Smoothed Word Embeddings for Low-Resource Settings—0
Distributed representation of multi-sense words: A loss-driven approach—0
Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning—0
Domain Mismatch Doesn’t Always Prevent Cross-lingual Transfer Learning—0
Do Multi-Sense Embeddings Improve Natural Language Understanding?—0
Do Supervised Distributional Methods Really Learn Lexical Inference Relations?—0
Do We Need Neural Models to Explain Human Judgments of Acceptability?—0
DRCoVe: An Augmented Word Representation Approach using Distributional and Relational Context—0
EDS-MEMBED: Multi-sense embeddings based on enhanced distributional semantic structures via a graph walk over word senses—0
Effect of Post-processing on Contextualized Word Representations—0
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space—0
Embedding Learning Through Multilingual Concept Induction—0
Embeddings models for Buddhist Sanskrit—0
Embedding Word Similarity with Neural Machine Translation—0
Embracing Error to Enable Rapid Crowdsourcing—0
Evaluating Ways of Adapting Word Similarity—0
Evaluation of Morphological Embeddings for English and Russian Languages—0
Evaluation of taxonomic and neural embedding methods for calculating semantic similarity—0
Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks—0
EVALution-MAN: A Chinese Dataset for the Training and Evaluation of DSMs—0
Expansional Retrofitting for Word Vector Enrichment—0
Explicit Retrofitting of Distributional Word Vectors—0
Exploring Transformers for Ranking Portuguese Semantic Relations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Context-to-VectorSpearman's Rho78.9—Unverified
2Bert2VecSpearman's Rho72.8—Unverified
3SkipGramSpearman's Rho61—Unverified