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 151175 of 1564 papers

TitleStatusHype
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural NetworksCode1
Reinforcement Learning-powered Semantic Communication via Semantic SimilarityCode1
When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?Code1
Semantic-Preserving Adversarial Text AttacksCode1
Instance Similarity Learning for Unsupervised Feature RepresentationCode1
DECAF: Deep Extreme Classification with Label FeaturesCode1
Multimodal Representation for Neural Code SearchCode1
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
Catch-A-Waveform: Learning to Generate Audio from a Single Short ExampleCode1
Entity Concept-enhanced Few-shot Relation ExtractionCode1
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical InferenceCode1
A Semantic-based Method for Unsupervised Commonsense Question AnsweringCode1
Cross-lingual Text Classification with Heterogeneous Graph Neural NetworkCode1
Long Text Generation by Modeling Sentence-Level and Discourse-Level CoherenceCode1
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple OntologiesCode1
Paraphrastic Representations at ScaleCode1
Evaluating Document Representations for Content-based Legal Literature RecommendationsCode1
Semantic similarity metrics for learned image registrationCode1
R&R: Metric-guided Adversarial Sentence GenerationCode1
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence EncodersCode1
SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point CloudsCode1
Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language ModelsCode1
Automated radiology report generation using conditioned transformersCode1
PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERTCode1
On Semantic Similarity in Video RetrievalCode1
Show:102550
← PrevPage 7 of 63Next →

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