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 751–760 of 1564 papers

Title	Date	Tasks	Status
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase	Apr 16, 2021	Data Augmentationintent-classification	—Unverified
Instance Cross Entropy for Deep Metric Learning	Nov 22, 2019	Metric LearningSemantic Similarity	—Unverified
Instance-aware Image and Sentence Matching with Selective Multimodal LSTM	Nov 17, 2016	Semantic SimilaritySemantic Textual Similarity	—Unverified
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning	Jun 26, 2025	cross-modal alignmentRepresentation Learning	—Unverified
InsightNet: Structured Insight Mining from Customer Feedback	May 12, 2024	Semantic SimilaritySemantic Textual Similarity	—Unverified
InsertRank: LLMs can reason over BM25 scores to Improve Listwise Reranking	Jun 17, 2025	Information RetrievalReranking	—Unverified
Czech News Dataset for Semantic Textual Similarity	Aug 19, 2021	Semantic SimilaritySemantic Textual Similarity	—Unverified
Just an Update on PMING Distance for Web-based Semantic Similarity in Artificial Intelligence and Data Mining	Jan 9, 2017	Information RetrievalRetrieval	—Unverified
Autoencoding Low-Resolution MRI for Semantically Smooth Interpolation of Anisotropic MRI	Feb 18, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization	Jan 22, 2021	Learning-To-RankMulti-class Classification	—Unverified

Show:10 25 50

← PrevPage 76 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