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 751–800 of 1564 papers

TitleStatusHype
Semantic Similarity-Based Clustering of Findings From Security Testing Tools—0
SDM-Net: A Simple and Effective Model for Generalized Zero-Shot Learning—0
Semantic Similarity Computation for Abstract and Concrete Nouns Using Network-based Distributional Semantic Models—0
Semantic Similarity Computing for Scientific Academic Conferences fused with domain features—0
Semantic Similarity Computing Model Based on Multi Model Fine-Grained Nonlinear Fusion—0
Semantic similarity estimation for domain specific data using BERT and other techniques—0
Semantic Similarity from Natural Language and Ontology Analysis—0
Semantic Similarity Matching for Patent Documents Using Ensemble BERT-related Model and Novel Text Processing Method—0
Semantic Similarity Measure of Natural Language Text through Machine Learning and a Keyword-Aware Cross-Encoder-Ranking Summarizer -- A Case Study Using UCGIS GIS&T Body of Knowledge—0
Semantic Similarity Measures Applied to an Ontology for Human-Like Interaction—0
Semantic Similarity Models for Depression Severity Estimation—0
Semantic Similarity of Arabic Sentences with Word Embeddings—0
Semantic Similarity Score for Measuring Visual Similarity at Semantic Level—0
Semantic Similarity Strategies for Job Title Classification—0
Semantic Similarity To Improve Question Understanding in a Virtual Patient—0
Semantics in Multi-objective Genetic Programming—0
Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints—0
Semantic Stealth: Adversarial Text Attacks on NLP Using Several Methods—0
Semantic Text Transmission via Prediction with Small Language Models: Cost-Similarity Trade-off—0
SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching—0
SemCSE: Semantic Contrastive Sentence Embeddings Using LLM-Generated Summaries For Scientific Abstracts—0
SemEval-2014 Task 3: Cross-Level Semantic Similarity—0
SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)—0
SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity—0
SemEval-2018 Task 10: Capturing Discriminative Attributes—0
SEMILAR: The Semantic Similarity Toolkit—0
Semi-Supervised Clustering with Neural Networks—0
Semi-Supervised Generative Adversarial Hashing for Image Retrieval—0
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference—0
Semi-supervised lung nodule retrieval—0
SemR-11: A Multi-Lingual Gold-Standard for Semantic Similarity and Relatedness for Eleven Languages—0
SemSim: Resources for Normalized Semantic Similarity Computation Using Lexical Networks—0
SemSim: Revisiting Weak-to-Strong Consistency from a Semantic Similarity Perspective for Semi-supervised Medical Image Segmentation—0
SemTagger: A Novel Approach for Semantic Similarity Based Hashtag Recommendation on Twitter—0
SentenceKV: Efficient LLM Inference via Sentence-Level Semantic KV Caching—0
Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts—0
Sentence Pair Embeddings Based Evaluation Metric for Abstractive and Extractive Summarization—0
Sentence Similarity Based on Contexts—0
Sentiment Classification of Code-Switched Text using Pre-trained Multilingual Embeddings and Segmentation—0
SentSim: Crosslingual Semantic Evaluation of Machine Translation—0
SEOE: A Scalable and Reliable Semantic Evaluation Framework for Open Domain Event Detection—0
Seq2Seq-SC: End-to-End Semantic Communication Systems with Pre-trained Language Model—0
Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering—0
Sequence Learning with RNNs for Medical Concept Normalization in User-Generated Texts—0
Sequence Spreading-Based Semantic Communication Under High RF Interference—0
Sequential Visual and Semantic Consistency for Semi-supervised Text Recognition—0
Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data—0
SIFiD: Reassess Summary Factual Inconsistency Detection with LLM—0
Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning—0
SimBow at SemEval-2017 Task 3: Soft-Cosine Semantic Similarity between Questions for Community Question Answering—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