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 501–525 of 1564 papers

TitleStatusHype
Am\'elioration de la similarit\'e s\'emantique vectorielle par m\'ethodes non-supervis\'ees (Improved the Semantic Similarity with Weighting Vectors)—0
Evaluating distributed word representations for capturing semantics of biomedical concepts—0
A Deep Decomposable Model for Disentangling Syntax and Semantics in Sentence Representation—0
Corpus-Based Paraphrase Detection Experiments and Review—0
Evaluating Lexical Similarity to build Sentiment Similarity—0
Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering—0
Evaluating Retrieval Augmented Generative Models for Document Queries in Transportation Safety—0
Evaluating semantic models with word-sentence relatedness—0
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric—0
Evaluating text coherence based on semantic similarity graph—0
CORD19STS: COVID-19 Semantic Textual Similarity Dataset—0
Attention-aware semantic relevance predicting Chinese sentence reading—0
Ambiguity-Aware In-Context Learning with Large Language Models—0
Convolution-Enhanced Bilingual Recursive Neural Network for Bilingual Semantic Modeling—0
Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer—0
A Thesaurus for Biblical Hebrew—0
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models—0
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning—0
FBK-TR: Applying SVM with Multiple Linguistic Features for Cross-Level Semantic Similarity—0
Feature Engineering in Learning-to-Rank for Community Question Answering Task—0
A Text is Worth Several Tokens: Text Embedding from LLMs Secretly Aligns Well with The Key Tokens—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
A Massive Scale Semantic Similarity Dataset of Historical English—0
Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder—0
Contrastive Learning Subspace for Text Clustering—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