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 1126–1150 of 1564 papers

Title	Date	Tasks	Status	Hype
Term Based Semantic Clusters for Very Short Text Classification	Sep 1, 2019	ClassificationGeneral Classification	—Unverified	0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings	Sep 1, 2019	de-enMachine Translation	—Unverified	0
A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information	Sep 1, 2019	Binary ClassificationForm	—Unverified	0
Push for Quantization: Deep Fisher Hashing	Aug 31, 2019	QuantizationSemantic Similarity	—Unverified	0
Memorizing All for Implicit Discourse Relation Recognition	Aug 29, 2019	AllRelation	—Unverified	0
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks	Aug 27, 2019	ClusteringLinear-Probe Classification	CodeCode Available	1
A Method for Estimating the Proximity of Vector Representation Groups in Multidimensional Space. On the Example of the Paraphrase Task	Aug 25, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Phrase Localization Without Paired Training Examples	Aug 20, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Hamming Sentence Embeddings for Information Retrieval	Aug 15, 2019	DecoderInformation Retrieval	—Unverified	0
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding	Aug 14, 2019	Knowledge DistillationNatural Language Understanding	CodeCode Available	0
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric	Aug 12, 2019	DescriptiveDiversity	—Unverified	0
Interactive Variance Attention based Online Spoiler Detection for Time-Sync Comments	Aug 9, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources	Aug 1, 2019	Machine TranslationSemantic Similarity	—Unverified	0
MSnet: A BERT-based Network for Gendered Pronoun Resolution	Aug 1, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Specializing Distributional Vectors of All Words for Lexical Entailment	Aug 1, 2019	AllCross-Lingual Transfer	—Unverified	0
Context Effects on Human Judgments of Similarity	Aug 1, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Annotating and analyzing the interactions between meaning relations	Aug 1, 2019	Natural Language InferenceSemantic Similarity	CodeCode Available	0
A Hybrid Neural Network Model for Commonsense Reasoning	Jul 27, 2019	Common Sense ReasoningCoreference Resolution	—Unverified	0
VIFIDEL: Evaluating the Visual Fidelity of Image Descriptions	Jul 22, 2019	Image DescriptionSemantic Similarity	—Unverified	0
Analysis of Word Embeddings Using Fuzzy Clustering	Jul 17, 2019	ClusteringSemantic Similarity	—Unverified	0
DeepTrax: Embedding Graphs of Financial Transactions	Jul 16, 2019	BIG-bench Machine LearningFraud Detection	—Unverified	0
To Tune or Not To Tune? How About the Best of Both Worlds?	Jul 9, 2019	Language ModelingLanguage Modelling	CodeCode Available	0
Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases	Jul 6, 2019	Information RetrievalRetrieval	—Unverified	0
Using Thesaurus Data to Improve Coreference Resolution for Russian	Jul 1, 2019	coreference-resolutionCoreference Resolution	—Unverified	0
Assessing Wordnets with WordNet Embeddings	Jul 1, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	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