SOTAVerified

Word Similarity

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

Papers

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Showing 251–300 of 378 papers

TitleStatusHype
An Unsupervised Approach for Mapping between Vector Spaces—0
Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks—0
Learning Word Embeddings from Speech—0
Injecting Word Embeddings with Another Language's Resource : An Application of Bilingual Embeddings—0
Vertex-Context Sampling for Weighted Network Embedding—0
A Computational Study on Word Meanings and Their Distributed Representations via Polymodal Embedding—0
Replicability Analysis for Natural Language Processing: Testing Significance with Multiple DatasetsCode0
Semantic Composition via Probabilistic Model Theory—0
Word Re-Embedding via Manifold Dimensionality Retention—0
Word Embeddings based on Fixed-Size Ordinally Forgetting Encoding—0
Joint Embeddings of Chinese Words, Characters, and Fine-grained Subcharacter Components—0
Dict2vec : Learning Word Embeddings using Lexical DictionariesCode0
Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks—0
Joint Unsupervised Learning of Semantic Representation of Words and Roles in Dependency Trees—0
Simple and Effective Dimensionality Reduction for Word EmbeddingsCode0
Spectral Graph-Based Method of Multimodal Word Embedding—0
Jmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarityCode0
L2F/INESC-ID at SemEval-2017 Tasks 1 and 2: Lexical and semantic features in word and textual similarity—0
Learning Contextual Embeddings for Structural Semantic Similarity using Categorical Information—0
Learning Word Representations with Regularization from Prior Knowledge—0
HHU at SemEval-2017 Task 2: Fast Hash-Based Embeddings for Semantic Word Similarity Assessment—0
HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity—0
Mahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity—0
Wild Devs' at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity—0
An Artificial Language Evaluation of Distributional Semantic Models—0
QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding and Knowledge Base—0
RUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity by extending PMI and word embeddings systems with a Swadesh's-like list—0
SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity—0
Sew-Embed at SemEval-2017 Task 2: Language-Independent Concept Representations from a Semantically Enriched WikipediaCode0
Citius at SemEval-2017 Task 2: Cross-Lingual Similarity from Comparable Corpora and Dependency-Based Contexts—0
Improve Lexicon-based Word Embeddings By Word Sense Disambiguation—0
Learning Rare Word Representations using Semantic Bridging—0
Reconstruction of Word Embeddings from Sub-Word Parameters—0
A Critique of a Critique of Word Similarity Datasets: Sanity Check or Unnecessary Confusion?—0
A Simple Approach to Learn Polysemous Word EmbeddingsCode0
Improved Word Representation Learning with SememesCode0
Semantic Word Clusters Using Signed Spectral Clustering—0
Are distributional representations ready for the real world? Evaluating word vectors for grounded perceptual meaningCode0
Neural Embeddings of Graphs in Hyperbolic Space—0
Word Similarity Datasets for Indian Languages: Annotation and Baseline Systems—0
Predicting Emotional Word Ratings using Distributional Representations and Signed Clustering—0
Cross-Lingual Syntactically Informed Distributed Word Representations—0
Integrating Semantic Knowledge into Lexical Embeddings Based on Information Content MeasurementCode0
Reranking Translation Candidates Produced by Several Bilingual Word Similarity Sources—0
Construction of a Japanese Word Similarity DatasetCode0
How to evaluate word embeddings? On importance of data efficiency and simple supervised tasksCode0
All-but-the-Top: Simple and Effective Postprocessing for Word RepresentationsCode0
Implicitly Incorporating Morphological Information into Word Embedding—0
Real Multi-Sense or Pseudo Multi-Sense: An Approach to Improve Word Representation—0
Sub-Word Similarity based Search for Embeddings: Inducing Rare-Word Embeddings for Word Similarity Tasks and Language Modelling—0
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Benchmark Results

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