SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1151–1200 of 1564 papers

TitleStatusHype
Context Effects on Human Judgments of Similarity—0
A Hybrid Neural Network Model for Commonsense Reasoning—0
VIFIDEL: Evaluating the Visual Fidelity of Image Descriptions—0
Analysis of Word Embeddings Using Fuzzy Clustering—0
DeepTrax: Embedding Graphs of Financial Transactions—0
To Tune or Not To Tune? How About the Best of Both Worlds?Code0
Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases—0
Generating Natural Language Adversarial Examples through Probability Weighted Word SaliencyCode0
Aiming beyond the Obvious: Identifying Non-Obvious Cases in Semantic Similarity DatasetsCode0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
Using Thesaurus Data to Improve Coreference Resolution for Russian—0
Assessing Wordnets with WordNet EmbeddingsCode0
Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts—0
Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation—0
Visualising WordNet Embeddings: some preliminary results—0
Uncovering the Semantics of Wikipedia CategoriesCode0
Making Fast Graph-based Algorithms with Graph Metric EmbeddingsCode0
Learning Deep Multi-Level Similarity for Thermal Infrared Object TrackingCode0
A Semantic Cover Approach for Topic Modeling—0
Modeling performance differences on cognitive tests using LSTMs and skip-thought vectors trained on reported media consumption.—0
Classification of Semantic Paraphasias: Optimization of a Word Embedding Model—0
Toward a Computational Multidimensional Lexical Similarity Measure for Modeling Word Association Tasks in Psycholinguistics—0
GSI-UPM at SemEval-2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual Detection of Hate Speech Against Immigrants and Women on Twitter—0
Table2Vec: Neural Word and Entity Embeddings for Table Population and RetrievalCode0
Audio Caption in a Car Setting with a Sentence-Level LossCode0
Learning Multilingual Word Embeddings Using Image-Text Data—0
MultiWiki: Interlingual Text Passage Alignment in Wikipedia—0
Semantic flow in language networksCode0
Don't Blame Distributional Semantics if it can't do Entailment—0
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs—0
Knowledgeable Storyteller: A Commonsense-Driven Generative Model for Visual StorytellingCode0
Detecting Paraphrases of Standard Clause Titles in Insurance Contracts—0
Detecting Collocations Similarity via Logical-Linguistic Model—0
Model Comparison for Semantic GroupingCode0
Personalized Ranking in eCommerce Search—0
Supervised Online Hashing via Hadamard Codebook LearningCode0
Wasserstein-Fisher-Rao Document Distance—0
Deep Metric Learning Beyond Binary SupervisionCode0
Inpatient2Vec: Medical Representation Learning for Inpatients—0
MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations PredictionCode0
Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical StudyCode0
Word Similarity Datasets for Thai: Construction and EvaluationCode0
LICD: A Language-Independent Approach for Aspect Category Detection—0
Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning—0
Triplet-Based Deep Hashing Network for Cross-Modal Retrieval—0
A new approach for measuring semantic similarity of ontology concepts using dynamic programming—0
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence RepresentationsCode0
Learning semantic sentence representations from visually grounded language without lexical knowledgeCode0
Import2vec - Learning Embeddings for Software LibrariesCode0
Cross-modal Subspace Learning via Kernel Correlation Maximization and Discriminative Structure Preserving—0
Show:102550
← PrevPage 24 of 32Next →
All datasetsAnnotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICKBIOSSESCHIP-STSClinicalSTSMedSTS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F193.38—Unverified
2SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F191.51—Unverified
3SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F190.69—Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.16—Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.12—Unverified
#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.75—Unverified
2SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F186.8—Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F184.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Doc2VecCMSE0.31—Unverified
2LSTM (Tai et al., 2015)MSE0.28—Unverified
3Bidirectional LSTM (Tai et al., 2015)MSE0.27—Unverified
4combine-skip (Kiros et al., 2015)MSE0.27—Unverified
5Dependency Tree-LSTM (Tai et al., 2015)MSE0.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BioLinkBERT (large)Pearson Correlation0.94—Unverified
2BioLinkBERT (base)Pearson Correlation0.93—Unverified
3NCBI_BERT(base) (P+M)Pearson Correlation0.92—Unverified
#ModelMetricClaimedVerifiedStatus
1MacBERT-largeMacro F185.6—Unverified
#ModelMetricClaimedVerifiedStatus
1CharacterBERT (base, medical, ensemble)Pearson Correlation85.62—Unverified
#ModelMetricClaimedVerifiedStatus
1NCBI_BERT(base) (P+M)Pearson Correlation0.85—Unverified