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 1151–1175 of 1564 papers

Title	Date	Tasks	Status
Modeling performance differences on cognitive tests using LSTMs and skip-thought vectors trained on reported media consumption.	Jun 1, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified
Modeling Sentences in the Latent Space	Jul 1, 2012	Machine TranslationRetrieval	—Unverified
Modified Query Expansion Through Generative Adversarial Networks for Information Extraction in E-Commerce	Dec 30, 2022	Generative Adversarial NetworkSemantic Similarity	—Unverified
Monolingual alignment of word senses and definitions in lexicographical resources	Sep 6, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Moving Other Way: Exploring Word Mover Distance Extensions	Feb 7, 2022	ClassificationDocument Classification	—Unverified
MSD-1030: A Well-built Multi-Sense Evaluation Dataset for Sense Representation Models	May 1, 2020	Semantic SimilaritySemantic Textual Similarity	—Unverified
Multi-Attributed and Structured Text-to-Face Synthesis	Aug 25, 2021	DescriptiveDiversity	—Unverified
MultiGBS: A multi-layer graph approach to biomedical summarization	Aug 27, 2020	Extractive Text SummarizationSemantic Similarity	—Unverified
Multi-Label Transfer Learning for Multi-Relational Semantic Similarity	May 31, 2018	Multi-Task Learningregression	—Unverified
Multi-Level Graph Contrastive Learning	Jul 6, 2021	Contrastive LearningGraph Representation Learning	—Unverified
Multilingual Communication System with Deaf Individuals Utilizing Natural and Visual Languages	Dec 1, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Multilingual Corpus Creation for Multilingual Semantic Similarity Task	May 1, 2020	Semantic SimilaritySemantic Textual Similarity	—Unverified
Multilingual Financial Documentation Summarization by Team_Tredence for FNS2022	Jun 1, 2022	Abstractive Text SummarizationDocument Summarization	—Unverified
Multilinguality at Your Fingertips : BabelNet, Babelfy and Beyond !	Jun 1, 2015	Entity LinkingSemantic Similarity	—Unverified
Multi-Lingual Malaysian Embedding: Leveraging Large Language Models for Semantic Representations	Feb 5, 2024	RAGRetrieval	—Unverified
Multilingual Word Embeddings using Multigraphs	Dec 14, 2016	Machine TranslationMultilingual Word Embeddings	—Unverified
Multi-Modality Cross Attention Network for Image and Sentence Matching	Jun 1, 2020	Semantic SimilaritySemantic Textual Similarity	—Unverified
Multimodal Learning with Deep Boltzmann Machines	Dec 1, 2012	Information RetrievalRetrieval	—Unverified
Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition	Jun 22, 2024	Data AugmentationEEG	—Unverified
Multiple References with Meaningful Variations Improve Literary Machine Translation	Dec 24, 2024	Machine TranslationSemantic Similarity	—Unverified
Multiplex Graph Neural Network for Extractive Text Summarization	Aug 29, 2021	Extractive Text SummarizationGraph Neural Network	—Unverified
Multiscale Voxel Based Decoding For Enhanced Natural Image Reconstruction From Brain Activity	May 27, 2022	Generative Adversarial NetworkImage Reconstruction	—Unverified
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity	Mar 10, 2020	Cross-Lingual Word EmbeddingsRepresentation Learning	—Unverified
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity	Dec 1, 2020	Representation LearningSemantic Similarity	—Unverified
Multi-stage Distillation Framework for Cross-Lingual Semantic Similarity Matching	Nov 16, 2021	Contrastive LearningKnowledge Distillation	—Unverified

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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