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 1511–1520 of 1564 papers

Title	Date	Tasks	Status
SSMT:A Machine Translation Evaluation View To Paragraph-to-Sentence Semantic Similarity	Aug 1, 2014	Machine TranslationSemantic Similarity	—Unverified
SemEval-2014 Task 3: Cross-Level Semantic Similarity	Aug 1, 2014	Information RetrievalSemantic Similarity	—Unverified
FBK-TR: Applying SVM with Multiple Linguistic Features for Cross-Level Semantic Similarity	Aug 1, 2014	Information RetrievalMachine Translation	—Unverified
NTNU: Measuring Semantic Similarity with Sublexical Feature Representations and Soft Cardinality	Aug 1, 2014	Semantic SimilaritySemantic Textual Similarity	—Unverified
HulTech: A General Purpose System for Cross-Level Semantic Similarity based on Anchor Web Counts	Aug 1, 2014	Semantic SimilaritySemantic Textual Similarity	—Unverified
RTM-DCU: Referential Translation Machines for Semantic Similarity	Aug 1, 2014	Semantic SimilaritySemantic Textual Similarity	—Unverified
SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching	Aug 1, 2014	Question AnsweringSemantic Similarity	—Unverified
UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual Entailment	Aug 1, 2014	Information RetrievalMachine Translation	CodeCode Available
Predicting the relevance of distributional semantic similarity with contextual information	Jun 1, 2014	Information RetrievalSemantic Similarity	—Unverified
Weakly Supervised Multiclass Video Segmentation	Jun 1, 2014	SegmentationSemantic Similarity	—Unverified

Show:10 25 50

← PrevPage 152 of 157Next →

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