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 801–825 of 1564 papers

Title	Date	Tasks	Status
The Case for Perspective in Multimodal Datasets	May 22, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Neuro-Symbolic Artificial Intelligence (AI) for Intent based Semantic Communication	May 22, 2022	Semantic CommunicationSemantic Similarity	—Unverified
AEON: A Method for Automatic Evaluation of NLP Test Cases	May 13, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
Improving Contextual Representation with Gloss Regularized Pre-training	May 13, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Improving Relevance Quality in Product Search using High-Precision Query-Product Semantic Similarity	May 1, 2022	Re-RankingSemantic Similarity	—Unverified
Binary Encoded Word Mover’s Distance	May 1, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Rewarding Semantic Similarity under Optimized Alignments for AMR-to-Text Generation	May 1, 2022	AMR-to-Text GenerationReinforcement Learning (RL)	—Unverified
Probing Cross-Lingual Lexical Knowledge from Multilingual Sentence Encoders	Apr 30, 2022	Contrastive LearningCross-Lingual Entity Linking	—Unverified
Suggesting Relevant Questions for a Query Using Statistical Natural Language Processing Technique	Apr 26, 2022	Self-LearningSemantic Similarity	—Unverified
Word Embeddings and Validity Indexes in Fuzzy Clustering	Apr 26, 2022	ClusteringSemantic Similarity	—Unverified
A Multi-level Alignment Training Scheme for Video-and-Language Grounding	Apr 22, 2022	RetrievalSemantic Similarity	—Unverified
Adversarial Contrastive Learning by Permuting Cluster Assignments	Apr 21, 2022	Computational EfficiencyContrastive Learning	—Unverified
What If: Generating Code to Answer Simulation Questions	Apr 16, 2022	Program SynthesisSemantic Similarity	CodeCode Available
Farmer-Bot: An Interactive Bot for Farmers	Apr 7, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Efficient comparison of sentence embeddings	Apr 2, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Analyzing how BERT performs entity matching	Apr 1, 2022	Entity ResolutionSemantic Similarity	CodeCode Available
Semantic Pose Verification for Outdoor Visual Localization with Self-supervised Contrastive Learning	Mar 31, 2022	Contrastive LearningSemantic Similarity	—Unverified
A bilingual approach to specialised adjectives through word embeddings in the karstology domain	Mar 31, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified
Cross-Media Scientific Research Achievements Retrieval Based on Deep Language Model	Mar 29, 2022	Cross-Modal RetrievalLanguage Modeling	—Unverified
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph Distance	Mar 24, 2022	ClusteringData Augmentation	CodeCode Available
Semantic Similarity Computing for Scientific Academic Conferences fused with domain features	Mar 21, 2022	Keyword ExtractionSemantic Similarity	—Unverified
From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains	Mar 20, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
Scientific and Technological Information Oriented Semantics-adversarial and Media-adversarial Cross-media Retrieval	Mar 16, 2022	Information RetrievalRetrieval	—Unverified
SimMatch: Semi-supervised Learning with Similarity Matching	Mar 14, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
'Tis but Thy Name: Semantic Question Answering Evaluation with 11M Names for 1M Entities	Feb 28, 2022	Question AnsweringSemantic Similarity	—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