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 476–500 of 1564 papers

TitleStatusHype
CPN-CORE: A Text Semantic Similarity System Infused with Opinion Knowledge—0
Emphasizing Complementary Samples for Non-literal Cross-modal Retrieval—0
Brotherhood at WMT 2024: Leveraging LLM-Generated Contextual Conversations for Cross-Lingual Image Captioning—0
Attention-based Cross-Layer Domain Alignment for Unsupervised Domain Adaptation—0
EnDive: A Cross-Dialect Benchmark for Fairness and Performance in Large Language Models—0
End-To-End Graph-based Deep Semi-Supervised Learning—0
Building a Synthetic Biomedical Research Article Citation Linkage Corpus—0
Enhanced Word Representations for Bridging Anaphora Resolution—0
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval—0
Enhancing End-to-End Multi-Task Dialogue Systems: A Study on Intrinsic Motivation Reinforcement Learning Algorithms for Improved Training and Adaptability—0
Enhancing Health Information Retrieval with RAG by Prioritizing Topical Relevance and Factual Accuracy—0
Am\'elioration de la similarit\'e s\'emantique vectorielle par m\'ethodes non-supervis\'ees (Improved the Semantic Similarity with Weighting Vectors)—0
Enhancing user creativity: Semantic measures for idea generation—0
A Deep Decomposable Model for Disentangling Syntax and Semantics in Sentence Representation—0
Building Semantic Grams of Human Knowledge—0
Equation Embeddings—0
Building Static Embeddings from Contextual Ones: Is It Useful for Building Distributional Thesauri?—0
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games—0
Estimating Quality in Therapeutic Conversations: A Multi-Dimensional Natural Language Processing Framework—0
Calculating Semantic Similarity between Academic Articles using Topic Event and Ontology—0
Estimating Text Similarity based on Semantic Concept Embeddings—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
Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning—0
Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalization—0
Corpus-Based Paraphrase Detection Experiments and Review—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