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 851–900 of 1564 papers

TitleStatusHype
Reinforce Attack: Adversarial Attack against BERT with Reinforcement Learning—0
Semantic Answer Similarity for Evaluating Question Answering Models—0
Instance Similarity Learning for Unsupervised Feature RepresentationCode1
Semantic Similarity Based Evaluation for Abstractive News SummarizationCode0
System Description for the CommonGen task with the POINTER model—0
Text-in-Context: Token-Level Error Detection for Table-to-Text GenerationCode0
Explanations for CommonsenseQA: New Dataset and Models—0
DECAF: Deep Extreme Classification with Label FeaturesCode1
Term Expansion and FinBERT fine-tuning for Hypernym and Synonym Ranking of Financial TermsCode0
Seed Words Based Data Selection for Language Model Adaptation—0
Multi-Level Graph Contrastive Learning—0
Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning ModelsCode0
Multimodal Representation for Neural Code SearchCode1
DTAFA: Decoupled Training Architecture for Efficient FAQ Retrieval—0
Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder—0
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning—0
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic lossCode0
Investigating the Role of Negatives in Contrastive Representation Learning—0
Enhancing user creativity: Semantic measures for idea generation—0
Semantic sentence similarity: size does not always matter—0
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
Catch-A-Waveform: Learning to Generate Audio from a Single Short ExampleCode1
Entity Concept-enhanced Few-shot Relation ExtractionCode1
The Struggle with Academic Plagiarism: Approaches based on Semantic Similarity—0
Topic-Aware Evidence Reasoning and Stance-Aware Aggregation for Fact VerificationCode0
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical InferenceCode1
Looking for a Role for Word Embeddings in Eye-Tracking Features Prediction: Does Semantic Similarity Help?—0
Dissociating Semantic and Phonemic Search Strategies in the Phonemic Verbal Fluency Task in early Dementia—0
SentSim: Crosslingual Semantic Evaluation of Machine Translation—0
Corpus-Based Paraphrase Detection Experiments and Review—0
A Semantic-based Method for Unsupervised Commonsense Question AnsweringCode1
Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video Parsing—0
Cross-lingual Text Classification with Heterogeneous Graph Neural NetworkCode1
Augmenting Modelers with Semantic Autocompletion of Processes—0
Long Text Generation by Modeling Sentence-Level and Discourse-Level CoherenceCode1
Sentence Similarity Based on Contexts—0
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple OntologiesCode1
Measuring Economic Policy Uncertainty Using an Unsupervised Word Embedding-based Method—0
Informative and Representative Triplet Selection for Multilabel Remote Sensing Image RetrievalCode0
Semantics in Multi-objective Genetic Programming—0
Global and Local Information Adjustment for Semantic Similarity EvaluationCode0
Embedding Semantic Hierarchy in Discrete Optimal Transport for Risk Minimization—0
Paraphrastic Representations at ScaleCode1
Evaluating Contrastive Models for Instance-based Image Retrieval—0
CAT: Cross-Attention Transformer for One-Shot Object Detection—0
Evaluating Document Representations for Content-based Legal Literature RecommendationsCode1
More Than Meets The Eye: Semi-supervised Learning Under Non-IID DataCode0
Semantic similarity metrics for learned image registrationCode1
R&R: Metric-guided Adversarial Sentence GenerationCode1
Frequency-based Distortions in Contextualized Word Embeddings—0
Show:102550
← PrevPage 18 of 32Next →
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