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

Showing 15011525 of 1564 papers

TitleStatusHype
A web-based tool to Analyze Semantic Similarity Networks0
Probabilistic Models of Cross-Lingual Semantic Similarity in Context Based on Latent Cross-Lingual Concepts Induced from Comparable Data0
SAIL: Sentiment Analysis using Semantic Similarity and Contrast Features0
Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor0
Duluth : Measuring Cross-Level Semantic Similarity with First and Second Order Dictionary Overlaps0
The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity0
JU-Evora: A Graph Based Cross-Level Semantic Similarity Analysis using Discourse Information0
AI-KU: Using Co-Occurrence Modeling for Semantic Similarity0
ECNU: Leveraging on Ensemble of Heterogeneous Features and Information Enrichment for Cross Level Semantic Similarity Estimation0
DIT: Summarisation and Semantic Expansion in Evaluating Semantic Similarity0
SSMT:A Machine Translation Evaluation View To Paragraph-to-Sentence Semantic Similarity0
SemEval-2014 Task 3: Cross-Level Semantic Similarity0
FBK-TR: Applying SVM with Multiple Linguistic Features for Cross-Level Semantic Similarity0
NTNU: Measuring Semantic Similarity with Sublexical Feature Representations and Soft Cardinality0
HulTech: A General Purpose System for Cross-Level Semantic Similarity based on Anchor Web Counts0
RTM-DCU: Referential Translation Machines for Semantic Similarity0
SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching0
UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual EntailmentCode0
Predicting the relevance of distributional semantic similarity with contextual information0
Weakly Supervised Multiclass Video Segmentation0
Word Semantic Similarity for Morphologically Rich Languages0
Creative language explorations through a high-expressivity N-grams query language0
On Paraphrase Identification Corpora0
Using Entropy Estimates for DAG-Based Ontologies0
An evaluative baseline for geo-semantic relatedness and similarity0
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Benchmark Results

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