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 1251–1275 of 1564 papers

Title	Date	Tasks	Status	Hype
The Corpus Replication Task	Jun 20, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Improving Language Understanding by Generative Pre-Training	Jun 11, 2018	Cloze TestDocument Classification	CodeCode Available	1
Deploying Deep Ranking Models for Search Verticals	Jun 6, 2018	BIG-bench Machine LearningSemantic Similarity	—Unverified	0
Semi-Supervised Clustering with Neural Networks	Jun 5, 2018	ClusteringDeep Clustering	—Unverified	0
GKR: the Graphical Knowledge Representation for semantic parsing	Jun 1, 2018	Natural Language InferenceSemantic Parsing	—Unverified	0
Measuring Frame Instance Relatedness	Jun 1, 2018	ClusteringReading Comprehension	—Unverified	0
THU\_NGN at SemEval-2018 Task 10: Capturing Discriminative Attributes with MLP-CNN model	Jun 1, 2018	AttributeSemantic Similarity	—Unverified	0
UniMelb at SemEval-2018 Task 12: Generative Implication using LSTMs, Siamese Networks and Semantic Representations with Synonym Fuzzing	Jun 1, 2018	General ClassificationMulti-Task Learning	—Unverified	0
SemEval-2018 Task 10: Capturing Discriminative Attributes	Jun 1, 2018	AttributeSemantic Similarity	—Unverified	0
Similarity Measures for the Detection of Clinical Conditions with Verbal Fluency Tasks	Jun 1, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models	Jun 1, 2018	General ClassificationSemantic Similarity	—Unverified	0
Specialising Word Vectors for Lexical Entailment	Jun 1, 2018	Dialogue State TrackingLexical Entailment	CodeCode Available	0
Multi-Label Transfer Learning for Multi-Relational Semantic Similarity	May 31, 2018	Multi-Task Learningregression	—Unverified	0
Legal Document Retrieval using Document Vector Embeddings and Deep Learning	May 27, 2018	Deep LearningInformation Retrieval	—Unverified	0
R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering	May 24, 2018	Question AnsweringRelation	CodeCode Available	1
Weight Initialization in Neural Language Models	May 12, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
A Rank-Based Similarity Metric for Word Embeddings	May 4, 2018	ClusteringOutlier Detection	—Unverified	0
Semantic Structure-based Unsupervised Deep Hashing	May 1, 2018	Deep HashingSemantic Similarity	CodeCode Available	0
SemR-11: A Multi-Lingual Gold-Standard for Semantic Similarity and Relatedness for Eleven Languages	May 1, 2018	Information RetrievalMachine Translation	—Unverified	0
OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction	Apr 29, 2018	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages	Apr 27, 2018	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Learning Semantic Textual Similarity from Conversations	Apr 20, 2018	Community Question AnsweringNatural Language Inference	CodeCode Available	0
Direct Network Transfer: Transfer Learning of Sentence Embeddings for Semantic Similarity	Apr 20, 2018	Natural Language UnderstandingSemantic Similarity	—Unverified	0
Similarity between Learning Outcomes from Course Objectives using Semantic Analysis, Blooms taxonomy and Corpus statistics	Apr 17, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Introducing two Vietnamese Datasets for Evaluating Semantic Models of (Dis-)Similarity and Relatedness	Apr 15, 2018	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