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 1151–1175 of 1564 papers

TitleStatusHype
A Survey on Text Simplification—0
ATEB: Evaluating and Improving Advanced NLP Tasks for Text Embedding Models—0
A text autoencoder from transformer for fast encoding language representation—0
A Text is Worth Several Tokens: Text Embedding from LLMs Secretly Aligns Well with The Key Tokens—0
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning—0
A Thesaurus for Biblical Hebrew—0
Attention-aware semantic relevance predicting Chinese sentence reading—0
Attention-based Cross-Layer Domain Alignment for Unsupervised Domain Adaptation—0
Attention Discriminant Sampling for Point Clouds—0
Attribute-Graph: A Graph based approach to Image Ranking—0
Augmenting Modelers with Semantic Autocompletion of Processes—0
Author-aware Aspect Topic Sentiment Model to Retrieve Supporting Opinions from Reviews—0
AuthorMist: Evading AI Text Detectors with Reinforcement Learning—0
Autoencoder-Based Domain Learning for Semantic Communication with Conceptual Spaces—0
Autoencoding Low-Resolution MRI for Semantically Smooth Interpolation of Anisotropic MRI—0
Automated Feedback Loops to Protect Text Simplification with Generative AI from Information Loss—0
Xu: An Automated Query Expansion and Optimization Tool—0
Automatic Difficulty Classification of Arabic Sentences—0
Automatic Real-word Error Correction in Persian Text—0
Automatic Visual Theme Discovery from Joint Image and Text Corpora—0
Automating the Compilation of Potential Core-Outcomes for Clinical Trials—0
Automating Transfer Credit Assessment in Student Mobility -- A Natural Language Processing-based Approach—0
A Vector Space for Distributional Semantics for Entailment—0
A weakly supervised adaptive triplet loss for deep metric learning—0
A web-based tool to Analyze Semantic Similarity Networks—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