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 15211530 of 1564 papers

TitleStatusHype
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
Semantic Similarity Measures Applied to an Ontology for Human-Like Interaction0
The semantic similarity ensemble0
What implementation and translation teach us: the case of semantic similarity measures in wordnets0
Evaluation on Second Language Collocational Congruency with Computational Semantic Similarity0
Description and Evaluation of Semantic Similarity Measures ApproachesCode0
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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 cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3Unverified
3SciBERT uncased (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