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 1101–1125 of 1564 papers

Title	Date	Tasks	Status
A Bilingual Generative Transformer for Semantic Sentence Embedding	Nov 10, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines	Nov 10, 2019	Few-Shot LearningLanguage Modeling	CodeCode Available
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation	Nov 8, 2019	Articlescounterfactual	—Unverified
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning	Nov 8, 2019	Linguistic AcceptabilityNatural Language Inference	—Unverified
Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks	Nov 7, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified
Gextext: Disease Network Extraction from Biomedical Literature	Nov 6, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified
Machine Translation Evaluation using Bi-directional Entailment	Nov 2, 2019	Machine TranslationSemantic Similarity	—Unverified
Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling	Nov 1, 2019	Natural Language InferenceQuestion Answering	—Unverified
Towards Actual (Not Operational) Textual Style Transfer Auto-Evaluation	Nov 1, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified
Team GPLSI. Approach for automated fact checking	Nov 1, 2019	ArticlesFact Checking	—Unverified
Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach	Nov 1, 2019	Meta-LearningSemantic Similarity	—Unverified
Wasserstein distances for evaluating cross-lingual embeddings	Oct 24, 2019	Cross-Lingual Document ClassificationDocument Classification	—Unverified
A Novel Approach for Automatic Bengali Question Answering System using Semantic Similarity Analysis	Oct 23, 2019	POSPOS Tagging	—Unverified
A Comparison of Semantic Similarity Methods for Maximum Human Interpretability	Oct 21, 2019	Information RetrievalRetrieval	—Unverified
Textual analysis of artificial intelligence manuscripts reveals features associated with peer review outcome	Oct 21, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
Universal Text Representation from BERT: An Empirical Study	Oct 17, 2019	Learning-To-RankNatural Language Inference	—Unverified
Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations	Oct 17, 2019	Deep LearningSemantic Similarity	—Unverified
Learning Analogy-Preserving Sentence Embeddings for Answer Selection	Oct 11, 2019	Answer SelectionQuestion Answering	—Unverified
Domain-Relevant Embeddings for Medical Question Similarity	Oct 9, 2019	Question AnsweringQuestion Similarity	—Unverified
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding	Oct 8, 2019	Domain AdaptationDynamic graph embedding	—Unverified
A weakly supervised adaptive triplet loss for deep metric learning	Sep 27, 2019	Metric LearningRetrieval	—Unverified
Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions	Sep 19, 2019	Community Question AnsweringQuestion Answering	—Unverified
Semantic Relatedness Based Re-ranker for Text Spotting	Sep 17, 2019	ClusteringDimensionality Reduction	CodeCode Available
Hashtags are (not) judgemental: The untold story of Lok Sabha elections 2019	Sep 16, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified
Where are the Keys? -- Learning Object-Centric Navigation Policies on Semantic Maps with Graph Convolutional Networks	Sep 16, 2019	ObjectSemantic Similarity	CodeCode Available

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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