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 201–225 of 1564 papers

Title	Date	Tasks	Status	Hype
SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization	May 7, 2020	Document SummarizationMulti-Document Summarization	CodeCode Available	1
Neural CRF Model for Sentence Alignment in Text Simplification	May 5, 2020	ArticlesSemantic Similarity	CodeCode Available	1
Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction	May 4, 2020	Language ModelingLanguage Modelling	CodeCode Available	1
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation	May 3, 2020	Cross-Lingual TransferLanguage Modeling	CodeCode Available	1
Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO	Apr 30, 2020	Image CaptioningRepresentation Learning	CodeCode Available	1
Word Rotator's Distance	Apr 30, 2020	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
Fast and Accurate Deep Bidirectional Language Representations for Unsupervised Learning	Apr 17, 2020	CPULanguage Modeling	CodeCode Available	1
Attentive Normalization for Conditional Image Generation	Apr 8, 2020	Conditional Image GenerationImage Generation	CodeCode Available	1
Text-Guided Neural Image Inpainting	Apr 7, 2020	DescriptiveImage Generation	CodeCode Available	1
Semantic Pyramid for Image Generation	Mar 13, 2020	General ClassificationImage Generation	CodeCode Available	1
Generalized Product Quantization Network for Semi-supervised Image Retrieval	Feb 26, 2020	Image RetrievalMetric Learning	CodeCode Available	1
Learning by Semantic Similarity Makes Abstractive Summarization Better	Feb 18, 2020	Abstractive Text SummarizationSemantic Similarity	CodeCode Available	1
Symmetrical Synthesis for Deep Metric Learning	Jan 31, 2020	ClusteringImage Retrieval	CodeCode Available	1
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks	Aug 27, 2019	ClusteringLinear-Probe Classification	CodeCode Available	1
Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets	Jun 13, 2019	BenchmarkingDocument Classification	CodeCode Available	1
Deep Metric Learning by Online Soft Mining and Class-Aware Attention	Nov 4, 2018	Metric LearningPerson Re-Identification	CodeCode Available	1
MedSTS: A Resource for Clinical Semantic Textual Similarity	Aug 28, 2018	Decision MakingSemantic Similarity	CodeCode Available	1
Improving Language Understanding by Generative Pre-Training	Jun 11, 2018	Cloze TestDocument Classification	CodeCode Available	1
R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering	May 24, 2018	Question AnsweringRelation	CodeCode Available	1
No Fuss Distance Metric Learning using Proxies	Mar 21, 2017	Metric LearningSemantic Similarity	CodeCode Available	1
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding	Feb 17, 2016	Entity TypingSemantic Similarity	CodeCode Available	1
Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy	Sep 20, 1997	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
SemCSE: Semantic Contrastive Sentence Embeddings Using LLM-Generated Summaries For Scientific Abstracts	Jul 17, 2025	Contrastive LearningSemantic Similarity	—Unverified	0
SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression	Jul 8, 2025	Evidence SelectionRAG	—Unverified	0
FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution Detection	Jul 6, 2025	Out-of-Distribution DetectionOut of Distribution (OOD) Detection	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