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 1226–1250 of 1564 papers

Title	Date	Tasks	Status	Hype
A Graph-theoretic Summary Evaluation for ROUGE	Oct 1, 2018	Abstractive Text SummarizationSemantic Similarity	—Unverified	0
Hierarchy-based Image Embeddings for Semantic Image Retrieval	Sep 26, 2018	Few-Shot LearningImage Retrieval	CodeCode Available	0
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA	Sep 12, 2018	Question AnsweringSemantic Similarity	—Unverified	0
Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints	Sep 4, 2018	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Hypernyms Through Intra-Article Organization in Wikipedia	Sep 3, 2018	ArticlesSemantic Similarity	—Unverified	0
Semi-Supervised Generative Adversarial Hashing for Image Retrieval	Sep 1, 2018	Deep HashingImage Retrieval	—Unverified	0
MedSTS: A Resource for Clinical Semantic Textual Similarity	Aug 28, 2018	Decision MakingSemantic Similarity	CodeCode Available	1
Xu: An Automated Query Expansion and Optimization Tool	Aug 28, 2018	ArticlesClustering	—Unverified	0
Learning Graph Embeddings from WordNet-based Similarity Measures	Aug 16, 2018	Graph EmbeddingSemantic Similarity	—Unverified	0
Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content	Aug 14, 2018	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
A Joint Sequence Fusion Model for Video Question Answering and Retrieval	Aug 7, 2018	DecoderMultiple-choice	CodeCode Available	0
An Efficient Approach to Learning Chinese Judgment Document Similarity Based on Knowledge Summarization	Aug 6, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activations	Aug 1, 2018	Dimensionality ReductionSemantic Similarity	CodeCode Available	0
GenSense: A Generalized Sense Retrofitting Model	Aug 1, 2018	modelSemantic Similarity	CodeCode Available	0
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings	Jul 31, 2018	Machine TranslationNMT	—Unverified	0
Clustering Prominent People and Organizations in Topic-Specific Text Corpora	Jul 27, 2018	ArticlesClustering	—Unverified	0
Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing	Jul 17, 2018	Multi-domain Dialogue State TrackingSemantic Similarity	CodeCode Available	0
Pangloss: Fast Entity Linking in Noisy Text Environments	Jul 16, 2018	ArticlesEntity Disambiguation	—Unverified	0
Learning Distributional Token Representations from Visual Features	Jul 1, 2018	Machine TranslationNMT	—Unverified	0
Injecting Lexical Contrast into Word Vectors by Guiding Vector Space Specialisation	Jul 1, 2018	Dialogue State TrackingRepresentation Learning	—Unverified	0
WordNet Embeddings	Jul 1, 2018	Representation LearningSemantic Similarity	CodeCode Available	0
A Spatial Model for Extracting and Visualizing Latent Discourse Structure in Text	Jul 1, 2018	Information RetrievalReading Comprehension	—Unverified	0
Learning Thematic Similarity Metric from Article Sections Using Triplet Networks	Jul 1, 2018	ArticlesClustering	—Unverified	0
Using pseudo-senses for improving the extraction of synonyms from word embeddings	Jul 1, 2018	Dimensionality ReductionSemantic Similarity	—Unverified	0
Paragraph-based complex networks: application to document classification and authenticity verification	Jun 22, 2018	DiversityDocument Classification	—Unverified	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 uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
3	SciBERT cased (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