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 101–125 of 1564 papers

Title	Date	Tasks	Status	Hype
Efficient Mask Correction for Click-Based Interactive Image Segmentation	Jan 1, 2023	Image SegmentationSegmentation	CodeCode Available	1
DIP: Dual Incongruity Perceiving Network for Sarcasm Detection	Jan 1, 2023	Sarcasm DetectionSemantic Similarity	CodeCode Available	1
Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning	Dec 21, 2022	Contrastive LearningLinear evaluation	CodeCode Available	1
Graph-based Semantical Extractive Text Analysis	Dec 19, 2022	Keyword ExtractionSemantic Similarity	CodeCode Available	1
Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora	Nov 29, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
Improving word mover's distance by leveraging self-attention matrix	Nov 11, 2022	Paraphrase IdentificationSemantic Similarity	CodeCode Available	1
RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question	Nov 2, 2022	Question AnsweringQuestion Generation	CodeCode Available	1
Pointly-Supervised Panoptic Segmentation	Oct 25, 2022	Panoptic SegmentationSegmentation	CodeCode Available	1
Describing Sets of Images with Textual-PCA	Oct 21, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
Weak-shot Semantic Segmentation via Dual Similarity Transfer	Oct 5, 2022	SegmentationSemantic Segmentation	CodeCode Available	1
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity Recognition	Oct 1, 2022	Contrastive Learningfew-shot-ner	CodeCode Available	1
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling	Sep 26, 2022	DecoderDepth Estimation	CodeCode Available	1
Ranking-Enhanced Unsupervised Sentence Representation Learning	Sep 9, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
MENLI: Robust Evaluation Metrics from Natural Language Inference	Aug 15, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Tackling Long-Tailed Category Distribution Under Domain Shifts	Jul 20, 2022	Domain GeneralizationMeta-Learning	CodeCode Available	1
Semantic Novelty Detection via Relational Reasoning	Jul 18, 2022	Autonomous DrivingEdge-computing	CodeCode Available	1
Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction	Jul 9, 2022	Explanation GenerationFairness	CodeCode Available	1
On the Effectiveness of Sentence Encoding for Intent Detection Meta-Learning	Jul 1, 2022	Intent DetectionMeta-Learning	CodeCode Available	1
SynWMD: Syntax-aware Word Mover's Distance for Sentence Similarity Evaluation	Jun 20, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1
Zero-shot object goal visual navigation	Jun 15, 2022	Knowledge GraphsObject	CodeCode Available	1
TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation	May 27, 2022	Machine TranslationSemantic Similarity	CodeCode Available	1
HIRL: A General Framework for Hierarchical Image Representation Learning	May 26, 2022	Image ClusteringRepresentation Learning	CodeCode Available	1
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
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
SANA: Cross-Species Prediction of Gene Ontology GO Annotations via Topological Network Alignment	Apr 26, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	1

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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