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 1051–1100 of 1564 papers

TitleStatusHype
A Thesaurus for Biblical Hebrew—0
Legal-ES: A Set of Large Scale Resources for Spanish Legal Text Processing—0
Towards Automatic Thesaurus Construction and Enrichment.—0
Extrapolating Binder Style Word Embeddings to New Words—0
Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCOCode1
Word Rotator's DistanceCode1
Combining Word Embeddings and N-grams for Unsupervised Document Summarization—0
Evolution of Semantic Similarity -- A Survey—0
Fast and Accurate Deep Bidirectional Language Representations for Unsupervised LearningCode1
Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric—0
Attentive Normalization for Conditional Image GenerationCode1
Text-Guided Neural Image InpaintingCode1
Beyond Background-Aware Correlation Filters: Adaptive Context Modeling by Hand-Crafted and Deep RGB Features for Visual Tracking—0
A random forest based computational model for predicting novel lncRNA-disease associationsCode0
Semantic Pyramid for Image GenerationCode1
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity—0
Unifying Specialist Image Embedding into Universal Image Embedding—0
Friend Recommendation based on Hashtags Analysis—0
Comment Ranking Diversification in Forum DiscussionsCode0
Generalized Product Quantization Network for Semi-supervised Image RetrievalCode1
A Quadruplet Loss for Enforcing Semantically Coherent Embeddings in Multi-output Classification ProblemsCode0
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction—0
Utilizing a null class to restrict decision spaces and defend against neural network adversarial attacksCode0
End-To-End Graph-based Deep Semi-Supervised Learning—0
Learning by Semantic Similarity Makes Abstractive Summarization BetterCode1
Symmetrical Synthesis for Deep Metric LearningCode1
Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding—0
Hybrid Semantic Recommender System for Chemical CompoundsCode0
Classifying Wikipedia in a fine-grained hierarchy: what graphs can contribute—0
User-in-the-loop Adaptive Intent Detection for Instructable Digital AssistantCode0
Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice machine reading comprehension—0
Open Domain Question Answering Using Web Tables—0
Ranking and Classification driven Feature Learning for Person Re_identificationCode0
MALA: Cross-Domain Dialogue Generation with Action Learning—0
Semantic Similarity To Improve Question Understanding in a Virtual Patient—0
Legal document retrieval across languages: topic hierarchies based on synsets—0
Instance Cross Entropy for Deep Metric Learning—0
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension—0
SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word EmbeddingsCode0
Weakly-Supervised Video Moment Retrieval via Semantic Completion Network—0
Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive BaselinesCode0
A Bilingual Generative Transformer for Semantic Sentence EmbeddingCode0
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation—0
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning—0
Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks—0
Gextext: Disease Network Extraction from Biomedical Literature—0
Machine Translation Evaluation using Bi-directional Entailment—0
Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach—0
Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling—0
Team GPLSI. Approach for automated fact checking—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