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 826–850 of 1564 papers

TitleStatusHype
Structure and Semantics Preserving Document Representations—0
Studying Lobby Influence in the European Parliament—0
Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric—0
Suggesting Relevant Questions for a Query Using Statistical Natural Language Processing Technique—0
SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail—0
Superpixel-Based Building Damage Detection from Post-earthquake Imagery Using Deep Neural Networks—0
SUPER-Rec: SUrrounding Position-Enhanced Representation for Recommendation—0
Supervised Machine Learning Algorithm for Detecting Consistency between Reported Findings and the Conclusions of Mammography Reports—0
SURF: Semantic-level Unsupervised Reward Function for Machine Translation—0
Graded Suspiciousness of Adversarial Texts to Human—0
Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similarity—0
System Description for the CommonGen task with the POINTER model—0
T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on an Assistant Task for a Target Task—0
TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity—0
TakeLab-QA at SemEval-2017 Task 3: Classification Experiments for Answer Retrieval in Community QA—0
Talla at SemEval-2017 Task 3: Identifying Similar Questions Through Paraphrase Detection—0
Targeted and Troublesome: Tracking and Advertising on Children's Websites—0
Task Formulation Matters When Learning Continuously: A Case Study in Visual Question Answering—0
Task-Oriented Intrinsic Evaluation of Semantic Textual Similarity—0
Team dina at SemEval-2022 Task 8: Pre-trained Language Models as Baselines for Semantic Similarity—0
Team GPLSI. Approach for automated fact checking—0
Temporal Analysis of Entity Relatedness and its Evolution using Wikipedia and DBpedia—0
Term Based Semantic Clusters for Very Short Text Classification—0
Testing the limits of unsupervised learning for semantic similarity—0
TexIm FAST: Text-to-Image Representation for Semantic Similarity Evaluation using Transformers—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 uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT cased (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