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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 876–900 of 1564 papers

Title	Date	Tasks	Status	Hype
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference	Jun 2, 2021	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
Looking for a Role for Word Embeddings in Eye-Tracking Features Prediction: Does Semantic Similarity Help?	Jun 1, 2021	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Dissociating Semantic and Phonemic Search Strategies in the Phonemic Verbal Fluency Task in early Dementia	Jun 1, 2021	ManagementSemantic Similarity	—Unverified	0
SentSim: Crosslingual Semantic Evaluation of Machine Translation	Jun 1, 2021	Machine TranslationSemantic Similarity	—Unverified	0
Corpus-Based Paraphrase Detection Experiments and Review	May 31, 2021	Authorship AttributionDeep Learning	—Unverified	0
A Semantic-based Method for Unsupervised Commonsense Question Answering	May 31, 2021	Question AnsweringSemantic Similarity	CodeCode Available	1
Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video Parsing	May 30, 2021	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Cross-lingual Text Classification with Heterogeneous Graph Neural Network	May 24, 2021	ClassificationGraph Neural Network	CodeCode Available	1
Augmenting Modelers with Semantic Autocompletion of Processes	May 24, 2021	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence	May 19, 2021	DecoderSemantic Similarity	CodeCode Available	1
Sentence Similarity Based on Contexts	May 17, 2021	Language ModelingLanguage Modelling	—Unverified	0
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies	May 11, 2021	Knowledge Graph EmbeddingsSemantic Similarity	CodeCode Available	1
Measuring Economic Policy Uncertainty Using an Unsupervised Word Embedding-based Method	May 10, 2021	ArticlesSemantic Similarity	—Unverified	0
Informative and Representative Triplet Selection for Multilabel Remote Sensing Image Retrieval	May 8, 2021	Image RetrievalMetric Learning	CodeCode Available	0
Semantics in Multi-objective Genetic Programming	May 6, 2021	Binary ClassificationDiversity	—Unverified	0
Global and Local Information Adjustment for Semantic Similarity Evaluation	May 1, 2021	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Embedding Semantic Hierarchy in Discrete Optimal Transport for Risk Minimization	Apr 30, 2021	image-classificationImage Classification	—Unverified	0
Paraphrastic Representations at Scale	Apr 30, 2021	CPUGPU	CodeCode Available	1
Evaluating Contrastive Models for Instance-based Image Retrieval	Apr 30, 2021	Image RetrievalRetrieval	—Unverified	0
CAT: Cross-Attention Transformer for One-Shot Object Detection	Apr 30, 2021	Objectobject-detection	—Unverified	0
Evaluating Document Representations for Content-based Legal Literature Recommendations	Apr 28, 2021	Recommendation SystemsRepresentation Learning	CodeCode Available	1
More Than Meets The Eye: Semi-supervised Learning Under Non-IID Data	Apr 20, 2021	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Semantic similarity metrics for learned image registration	Apr 20, 2021	Image RegistrationSemantic Similarity	CodeCode Available	1
R&R: Metric-guided Adversarial Sentence Generation	Apr 17, 2021	Adversarial AttackGeneral Classification	CodeCode Available	1
Frequency-based Distortions in Contextualized Word Embeddings	Apr 17, 2021	Semantic SimilaritySemantic Textual Similarity	—Unverified	0

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All datasets Annotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICK BIOSSES CHIP-STS ClinicalSTS MedSTS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	93.38	—	Unverified
2	SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	91.51	—	Unverified
3	SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	90.69	—	Unverified
4	BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	89.16	—	Unverified
5	BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	89.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.75	—	Unverified
2	SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
3	SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
4	BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	86.8	—	Unverified
5	BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	84.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Doc2VecC	MSE	0.31	—	Unverified
2	LSTM (Tai et al., 2015)	MSE	0.28	—	Unverified
3	Bidirectional LSTM (Tai et al., 2015)	MSE	0.27	—	Unverified
4	combine-skip (Kiros et al., 2015)	MSE	0.27	—	Unverified
5	Dependency Tree-LSTM (Tai et al., 2015)	MSE	0.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioLinkBERT (large)	Pearson Correlation	0.94	—	Unverified
2	BioLinkBERT (base)	Pearson Correlation	0.93	—	Unverified
3	NCBI_BERT(base) (P+M)	Pearson Correlation	0.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MacBERT-large	Macro F1	85.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CharacterBERT (base, medical, ensemble)	Pearson Correlation	85.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NCBI_BERT(base) (P+M)	Pearson Correlation	0.85	—	Unverified