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 1201–1250 of 1564 papers

TitleStatusHype
Comparison of State-of-the-Art Deep Learning APIs for Image Multi-Label Classification using Semantic MetricsCode0
Ranked List Loss for Deep Metric LearningCode0
EL Embeddings: Geometric construction of models for the Description Logic EL ++Code0
Investigating Antigram Behaviour using Distributional Semantics—0
ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translation—0
Hierarchy Neighborhood Discriminative Hashing for An Unified View of Single-Label and Multi-Label Image retrieval—0
Improving Context-Aware Semantic Relationships in Sparse Mobile Datasets—0
Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match—0
TextBugger: Generating Adversarial Text Against Real-world ApplicationsCode0
Temporal Analysis of Entity Relatedness and its Evolution using Wikipedia and DBpedia—0
MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs—0
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsCode0
A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions—0
Twitter-based traffic information system based on vector representations for words—0
Learning semantic similarity in a continuous space—0
Generative Models for Simulating Mobility Trajectories—0
Sequence Learning with RNNs for Medical Concept Normalization in User-Generated Texts—0
The MeSH-gram Neural Network Model: Extending Word Embedding Vectors with MeSH Concepts for UMLS Semantic Similarity and Relatedness in the Biomedical Domain—0
Generalised Differential Privacy for Text Document Processing—0
Not just a matter of semantics: the relationship between visual similarity and semantic similarity—0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Augmenting Neural Response Generation with Context-Aware Topical AttentionCode0
MindLab Neural Network Approach at BioASQ 6B—0
Efficient learning of neighbor representations for boundary trees and forests—0
Predicting the Semantic Textual Similarity with Siamese CNN and LSTM—0
A mathematical theory of semantic development in deep neural networksCode0
Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks—0
Improving Multilingual Semantic Textual Similarity with Shared Sentence Encoder for Low-resource Languages—0
Controlling Length in Abstractive Summarization Using a Convolutional Neural NetworkCode0
Auto-Encoding Dictionary Definitions into Consistent Word EmbeddingsCode0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
A Graph-theoretic Summary Evaluation for ROUGE—0
Hierarchy-based Image Embeddings for Semantic Image RetrievalCode0
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA—0
Generating More Interesting Responses in Neural Conversation Models with Distributional ConstraintsCode0
Hypernyms Through Intra-Article Organization in Wikipedia—0
Semi-Supervised Generative Adversarial Hashing for Image Retrieval—0
Xu: An Automated Query Expansion and Optimization Tool—0
Learning Graph Embeddings from WordNet-based Similarity Measures—0
Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia ContentCode0
A Joint Sequence Fusion Model for Video Question Answering and RetrievalCode0
An Efficient Approach to Learning Chinese Judgment Document Similarity Based on Knowledge Summarization—0
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activationsCode0
GenSense: A Generalized Sense Retrofitting ModelCode0
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings—0
Clustering Prominent People and Organizations in Topic-Specific Text Corpora—0
Large-Scale Multi-Domain Belief Tracking with Knowledge SharingCode0
Pangloss: Fast Entity Linking in Noisy Text Environments—0
Learning Distributional Token Representations from Visual Features—0
Using pseudo-senses for improving the extraction of synonyms from word embeddings—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