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 501–550 of 1564 papers

TitleStatusHype
GMFL-Net: A Global Multi-geometric Feature Learning Network for Repetitive Action CountingCode0
Guiding and Diversifying LLM-Based Story Generation via Answer Set ProgrammingCode0
Exploiting Semantic Role Contextualized Video Features for Multi-Instance Text-Video Retrieval EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022Code0
Global and Local Information Adjustment for Semantic Similarity EvaluationCode0
GMA3D: Local-Global Attention Learning to Estimate Occluded Motions of Scene FlowCode0
HACD: Harnessing Attribute Semantics and Mesoscopic Structure for Community DetectionCode0
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on TextCode0
Generating More Interesting Responses in Neural Conversation Models with Distributional ConstraintsCode0
EffEval: A Comprehensive Evaluation of Efficiency for MT Evaluation MetricsCode0
Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical StudyCode0
Generating Natural Language Adversarial Examples through Probability Weighted Word SaliencyCode0
From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and DomainsCode0
From Unimodal to Multimodal: Scaling up Projectors to Align ModalitiesCode0
Category-aware EEG image generation based on wavelet transform and contrast semantic lossCode0
Few-shot Hybrid Domain Adaptation of Image GeneratorsCode0
FAT ALBERT: Finding Answers in Large Texts using Semantic Similarity Attention Layer based on BERTCode0
A Quadruplet Loss for Enforcing Semantically Coherent Embeddings in Multi-output Classification ProblemsCode0
Temporally-Grounded Language Generation: A Benchmark for Real-Time Vision-Language ModelsCode0
Capturing Semantic Similarity for Entity Linking with Convolutional Neural NetworksCode0
FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented EnvironmentsCode0
FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation LearningCode0
GenSense: A Generalized Sense Retrofitting ModelCode0
Explaining Text Similarity in Transformer ModelsCode0
Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMsCode0
A random forest based computational model for predicting novel lncRNA-disease associationsCode0
HybridCR: Weakly-Supervised 3D Point Cloud Semantic Segmentation via Hybrid Contrastive RegularizationCode0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Evaluating text coherence based on semantic similarity graph—0
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric—0
Evaluating semantic models with word-sentence relatedness—0
Evaluating Retrieval Augmented Generative Models for Document Queries in Transportation Safety—0
Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network—0
Approximating Human-Like Few-shot Learning with GPT-based Compression—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 GenAI for Simplifying Texts for Education: Improving Accuracy and Consistency for Enhanced Readability—0
Can GPT models Follow Human Summarization Guidelines? Evaluating ChatGPT and GPT-4 for Dialogue Summarization—0
Approche supervis\'ee de calcul de similarit\'e s\'emantique entre paires de phrases (Supervised approach to compute semantic similarity between sentence pairs)—0
A Graph-theoretic Summary Evaluation for ROUGE—0
Evaluating distributed word representations for capturing semantics of biomedical concepts—0
Evaluating Deduplication Techniques for Economic Research Paper Titles with a Focus on Semantic Similarity using NLP and LLMs—0
Evaluating Contrastive Models for Instance-based Image Retrieval—0
Apport des ontologies pour le calcul de la similarité sémantique au sein d'un système de recommandation—0
Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning—0
\'Etat de l'art : mesures de similarit\'e s\'emantique locales et algorithmes globaux pour la d\'esambigu\" lexicale \`a base de connaissances (State of the art : Local Semantic Similarity Measures and Global Algorithmes for Knowledge-based Word Sense Disambiguation) [in French]—0
Estimating Text Similarity based on Semantic Concept Embeddings—0
Calculating Semantic Similarity between Academic Articles using Topic Event and Ontology—0
Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice machine reading comprehension—0
A Graph Based Semi-Supervised Approach for Analysis of Derivational Nouns in Sanskrit—0
A Comparison of Semantic Similarity Methods for Maximum Human Interpretability—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