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

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Showing 876–900 of 1564 papers

Title	Date	Tasks	Status
Towards a Gold Standard for Evaluating Danish Word Embeddings	May 1, 2020	Semantic SimilaritySemantic Textual Similarity	—Unverified
Towards Automated Patent Workflows: AI-Orchestrated Multi-Agent Framework for Intellectual Property Management and Analysis	Sep 21, 2024	Abstractive Text SummarizationKnowledge Graphs	—Unverified
Towards Automatic Thesaurus Construction and Enrichment.	May 1, 2020	Semantic SimilaritySemantic Textual Similarity	—Unverified
Towards explainable evaluation of language models on the semantic similarity of visual concepts	Sep 8, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models	Feb 26, 2025	Inference AttackMembership Inference Attack	—Unverified
Towards Semantic Communications: Deep Learning-Based Image Semantic Coding	Aug 8, 2022	Deep LearningImage Reconstruction	—Unverified
Towards Universal Dense Retrieval for Open-domain Question Answering	Sep 23, 2021	Open-Domain Question AnsweringQuestion Answering	—Unverified
Traffic event description based on Twitter data using Unsupervised Learning Methods for Indian road conditions	Dec 23, 2021	ManagementSemantic Similarity	—Unverified
Training a Ranking Function for Open-Domain Question Answering	Apr 12, 2018	Information RetrievalOpen-Domain Question Answering	—Unverified
Transfer Reward Learning for Policy Gradient-Based Text Generation	Sep 9, 2019	Conditional Text GenerationImage Captioning	—Unverified
Transformer-based Joint Source Channel Coding for Textual Semantic Communication	Jul 23, 2023	Semantic CommunicationSemantic Similarity	—Unverified
Transformers Can Compose Skills To Solve Novel Problems Without Finetuning	Sep 17, 2021	Question AnsweringSemantic Similarity	—Unverified
Transformer Semantic Genetic Programming for Symbolic Regression	Jan 30, 2025	regressionSemantic Similarity	—Unverified
Translating away Translationese without Parallel Data	Oct 28, 2023	Binary ClassificationLanguage Modelling	—Unverified
TrialMatchAI: An End-to-End AI-powered Clinical Trial Recommendation System to Streamline Patient-to-Trial Matching	May 13, 2025	Lightweight DeploymentRetrieval-augmented Generation	—Unverified
Triplet-Based Deep Hashing Network for Cross-Modal Retrieval	Apr 4, 2019	Cross-Modal RetrievalDeep Hashing	—Unverified
Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder	Jul 26, 2016	DecoderSemantic Similarity	—Unverified
Twitter-based traffic information system based on vector representations for words	Dec 4, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified
Two-stage Voice Application Recommender System for Unhandled Utterances in Intelligent Personal Assistant	Oct 19, 2021	Natural Language UnderstandingRecommendation Systems	—Unverified
Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems	Nov 15, 2022	Event DetectionGraph Neural Network	—Unverified
Typology of Adjectives Benchmark for Compositional Distributional Models	May 1, 2016	Semantic SimilaritySemantic Textual Similarity	—Unverified
uHelp: intelligent volunteer search for mutual help communities	Jan 26, 2023	Semantic SimilaritySemantic Textual Similarity	—Unverified
UMDeep at SemEval-2017 Task 1: End-to-End Shared Weight LSTM Model for Semantic Textual Similarity	Aug 1, 2017	Feature EngineeringMachine Translation	—Unverified
UMDuluth-BlueTeam: SVCSTS - A Multilingual and Chunk Level Semantic Similarity System	Jun 1, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
Unbiased Sentence Encoder For Large-Scale Multi-lingual Search Engines	Mar 1, 2021	Document RankingLanguage Modelling	—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