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 676–700 of 1564 papers

TitleStatusHype
IEKM: A Model Incorporating External Keyword Matrices—0
IHS-RD-Belarus at SemEval-2016 Task 1: Multistage Approach for Measuring Semantic Similarity—0
IIT (BHU): System Description for LSDSem'17 Shared Task—0
Fine-Grained ECG-Text Contrastive Learning via Waveform Understanding Enhancement—0
Image Generative Semantic Communication with Multi-Modal Similarity Estimation for Resource-Limited Networks—0
FindMeIfYouCan: Bringing Open Set metrics to near , far and farther Out-of-Distribution Object Detection—0
Finding the Topic of a Set of Images—0
Finding Salient Context based on Semantic Matching for Relevance Ranking—0
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings—0
Cross-Level Semantic Similarity for Serbian Newswire Texts—0
Improving Brain-to-Image Reconstruction via Fine-Grained Text Bridging—0
Integrating Distributional and Lexical Information for Semantic Classification of Words using MRMF—0
Improving Contextual Representation with Gloss Regularized Pre-training—0
Improving Contextual Representation with Gloss Regularized Pre-training—0
Improving Correlation with Human Judgments by Integrating Semantic Similarity with Second--Order Vectors—0
Internal Wasserstein Distance for Adversarial Attack and Defense—0
Improving Generalization of Image Captioning with Unsupervised Prompt Learning—0
Improving ICD-based semantic similarity by accounting for varying degrees of comorbidity—0
Improving Knowledge-Aware Dialogue Response Generation by Using Human-Written Prototype Dialogues—0
Investigating the Role of Negatives in Contrastive Representation Learning—0
Improving Legal Entity Recognition Using a Hybrid Transformer Model and Semantic Filtering Approach—0
Improving Long Document Topic Segmentation Models With Enhanced Coherence Modeling—0
Adaptive Logit Adjustment Loss for Long-Tailed Visual Recognition—0
Improving Multilingual Semantic Textual Similarity with Shared Sentence Encoder for Low-resource Languages—0
JUNITMZ at SemEval-2016 Task 1: Identifying Semantic Similarity Using Levenshtein Ratio—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