SOTAVerified

Semantic Similarity

The main objective Semantic Similarity is to measure the distance between the semantic meanings of a pair of words, phrases, sentences, or documents. For example, the word “car” is more similar to “bus” than it is to “cat”. The two main approaches to measuring Semantic Similarity are knowledge-based approaches and corpus-based, distributional methods.

Source: Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection

Papers

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Showing 1451–1500 of 1564 papers

TitleStatusHype
Evaluating Lexical Similarity to build Sentiment Similarity—0
Image Colorization Using a Deep Convolutional Neural Network—0
Scalable Gaussian Processes for Supervised Hashing—0
Capturing Semantic Similarity for Entity Linking with Convolutional Neural NetworksCode0
Evaluating semantic models with word-sentence relatedness—0
Counter-fitting Word Vectors to Linguistic ConstraintsCode0
Gibberish Semantics: How Good is Russian Twitter in Word Semantic Similarity Task?—0
Column sampling based discrete supervised hashing—0
Mapping it differently: A solution to the linking challenges—0
IndoWordNet::Similarity- Computing Semantic Similarity and Relatedness using IndoWordNet—0
Word Embeddings as Metric Recovery in Semantic Spaces—0
Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks—0
Learning Semantic Similarity for Very Short Texts—0
Let Sense Bags Do Talking: Cross Lingual Word Semantic Similarity for English and Hindi—0
Joint Word Representation Learning using a Corpus and a Semantic LexiconCode0
Attribute-Graph: A Graph based approach to Image Ranking—0
Zero-Shot Learning via Semantic Similarity Embedding—0
Measuring Semantic Similarity for Bengali Tweets Using WordNet—0
Better Summarization Evaluation with Word Embeddings for ROUGECode0
Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization—0
Exploratory topic modeling with distributional semantics—0
Exploring the effect of semantic similarity for Phrase-based Machine Translation—0
On metric embedding for boosting semantic similarity computations—0
Evaluating distributed word representations for capturing semantics of biomedical concepts—0
A density compensation-based path computing model for measuring semantic similarity—0
SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)—0
UMDuluth-BlueTeam: SVCSTS - A Multilingual and Chunk Level Semantic Similarity System—0
Multilinguality at Your Fingertips : BabelNet, Babelfy and Beyond !—0
RTM-DCU: Predicting Semantic Similarity with Referential Translation Machines—0
Sematch: Semantic Entity Search from Knowledge GraphCode0
An Open-source Framework for Multi-level Semantic Similarity Measurement—0
Paraphrase Identification and Semantic Similarity in Twitter with Simple Features—0
MathLingBudapest: Concept Networks for Semantic SimilarityCode0
FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter—0
Ebiquity: Paraphrase and Semantic Similarity in Twitter using Skipgrams—0
MITRE: Seven Systems for Semantic Similarity in Tweets—0
Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms—0
Aligning Sentences from Standard Wikipedia to Simple Wikipedia—0
So similar and yet incompatible: Toward the automated identification of semantically compatible words—0
NASARI: a Novel Approach to a Semantically-Aware Representation of Items—0
Random Walks and Neural Network Language Models on Knowledge Bases—0
Texts in, meaning out: neural language models in semantic similarity task for Russian—0
Joint Learning of Distributed Representations for Images and Texts—0
BitSim: An Algebraic Similarity Measure for Description Logics Concepts—0
Short Text Hashing Improved by Integrating Multi-Granularity Topics and TagsCode0
Context-Dependent Translation Selection Using Convolutional Neural Network—0
Improved Semantic Representations From Tree-Structured Long Short-Term Memory NetworksCode0
Probabilistic Zero-shot Classification with Semantic Rankings—0
Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval—0
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking—0
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All datasetsAnnotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICKBIOSSESCHIP-STSClinicalSTSMedSTS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F193.38—Unverified
2SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F191.51—Unverified
3SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F190.69—Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.16—Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.12—Unverified
#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.75—Unverified
2SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F186.8—Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F184.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Doc2VecCMSE0.31—Unverified
2LSTM (Tai et al., 2015)MSE0.28—Unverified
3Bidirectional LSTM (Tai et al., 2015)MSE0.27—Unverified
4combine-skip (Kiros et al., 2015)MSE0.27—Unverified
5Dependency Tree-LSTM (Tai et al., 2015)MSE0.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BioLinkBERT (large)Pearson Correlation0.94—Unverified
2BioLinkBERT (base)Pearson Correlation0.93—Unverified
3NCBI_BERT(base) (P+M)Pearson Correlation0.92—Unverified
#ModelMetricClaimedVerifiedStatus
1MacBERT-largeMacro F185.6—Unverified
#ModelMetricClaimedVerifiedStatus
1CharacterBERT (base, medical, ensemble)Pearson Correlation85.62—Unverified
#ModelMetricClaimedVerifiedStatus
1NCBI_BERT(base) (P+M)Pearson Correlation0.85—Unverified