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 701–725 of 1564 papers

Title	Date	Tasks	Status	Hype
Few-Shot Image Classification Benchmarks are Too Far From Reality: Build Back Better with Semantic Task Sampling	May 10, 2022	Few-Shot Image ClassificationGeneral Classification	CodeCode Available	1
Rewarding Semantic Similarity under Optimized Alignments for AMR-to-Text Generation	May 1, 2022	AMR-to-Text GenerationReinforcement Learning (RL)	—Unverified	0
A large-scale computational study of content preservation measures for text style transfer and paraphrase generation	May 1, 2022	Paraphrase GenerationSemantic Similarity	CodeCode Available	1
Binary Encoded Word Mover’s Distance	May 1, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Improving Relevance Quality in Product Search using High-Precision Query-Product Semantic Similarity	May 1, 2022	Re-RankingSemantic Similarity	—Unverified	0
Probing Cross-Lingual Lexical Knowledge from Multilingual Sentence Encoders	Apr 30, 2022	Contrastive LearningCross-Lingual Entity Linking	—Unverified	0
Word Embeddings and Validity Indexes in Fuzzy Clustering	Apr 26, 2022	ClusteringSemantic Similarity	—Unverified	0
SANA: Cross-Species Prediction of Gene Ontology GO Annotations via Topological Network Alignment	Apr 26, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
Suggesting Relevant Questions for a Query Using Statistical Natural Language Processing Technique	Apr 26, 2022	Self-LearningSemantic Similarity	—Unverified	0
A Multi-level Alignment Training Scheme for Video-and-Language Grounding	Apr 22, 2022	RetrievalSemantic Similarity	—Unverified	0
Adversarial Contrastive Learning by Permuting Cluster Assignments	Apr 21, 2022	Computational EfficiencyContrastive Learning	—Unverified	0
CgAT: Center-Guided Adversarial Training for Deep Hashing-Based Retrieval	Apr 18, 2022	Adversarial AttackAdversarial Defense	CodeCode Available	1
What If: Generating Code to Answer Simulation Questions	Apr 16, 2022	Program SynthesisSemantic Similarity	CodeCode Available	0
Farmer-Bot: An Interactive Bot for Farmers	Apr 7, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Towards Better Understanding of User Satisfaction in Open-Domain Conversational Search	Apr 6, 2022	Conversational SearchSemantic Similarity	CodeCode Available	1
Efficient comparison of sentence embeddings	Apr 2, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Analyzing how BERT performs entity matching	Apr 1, 2022	Entity ResolutionSemantic Similarity	CodeCode Available	0
Semantic Pose Verification for Outdoor Visual Localization with Self-supervised Contrastive Learning	Mar 31, 2022	Contrastive LearningSemantic Similarity	—Unverified	0
A bilingual approach to specialised adjectives through word embeddings in the karstology domain	Mar 31, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Cross-Media Scientific Research Achievements Retrieval Based on Deep Language Model	Mar 29, 2022	Cross-Modal RetrievalLanguage Modeling	—Unverified	0
LinkBERT: Pretraining Language Models with Document Links	Mar 29, 2022	Document ClassificationLanguage Modeling	CodeCode Available	2
Attributable Visual Similarity Learning	Mar 28, 2022	Metric LearningSemantic Similarity	CodeCode Available	1
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph Distance	Mar 24, 2022	ClusteringData Augmentation	CodeCode Available	0
Semantic Similarity Computing for Scientific Academic Conferences fused with domain features	Mar 21, 2022	Keyword ExtractionSemantic Similarity	—Unverified	0
From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains	Mar 20, 2022	Semantic SimilaritySemantic Textual Similarity	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