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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 776–800 of 1564 papers

TitleStatusHype
A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation – through the Lens of Semantic Similarity Rating—0
EMBEDDIA at SemEval-2022 Task 8: Investigating Sentence, Image, and Knowledge Graph Representations for Multilingual News Article SimilarityCode0
Learning Job Titles Similarity from Noisy Skill Labels—0
Team dina at SemEval-2022 Task 8: Pre-trained Language Models as Baselines for Semantic Similarity—0
Unsupervised Knowledge Graph Generation Using Semantic Similarity MatchingCode0
ValCAT: Variable-Length Contextualized Adversarial Transformations Using Encoder-Decoder Language ModelCode0
SURF: Semantic-level Unsupervised Reward Function for Machine Translation—0
Chinese Word Sense Embedding with SememeWSD and Synonym SetCode0
Exploiting Semantic Role Contextualized Video Features for Multi-Instance Text-Video Retrieval EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022Code0
Adversarial Self-Attention for Language UnderstandingCode0
Emphasizing Complementary Samples for Non-literal Cross-modal Retrieval—0
Knowledge Graph Fusion for Language Model Fine-tuning—0
Knowledge Graph Construction and Its Application in Automatic Radiology Report Generation from Radiologist's Dictation—0
Highlights of Semantics in Multi-objective Genetic Programming—0
Multilingual Financial Documentation Summarization by Team_Tredence for FNS2022—0
Sentence Pair Embeddings Based Evaluation Metric for Abstractive and Extractive Summarization—0
Building Static Embeddings from Contextual Ones: Is It Useful for Building Distributional Thesauri?—0
CLISTER : A Corpus for Semantic Textual Similarity in French Clinical Narratives—0
Building a Synthetic Biomedical Research Article Citation Linkage Corpus—0
Embeddings models for Buddhist Sanskrit—0
Cross-Level Semantic Similarity for Serbian Newswire Texts—0
Multiscale Voxel Based Decoding For Enhanced Natural Image Reconstruction From Brain Activity—0
Learning to segment with limited annotations: Self-supervised pretraining with regression and contrastive loss in MRI—0
Apport des ontologies pour le calcul de la similarité sémantique au sein d'un système de recommandation—0
A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation -- through the Lens of Semantic Similarity Rating—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 uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT cased (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