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

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Showing 1101–1150 of 1564 papers

TitleStatusHype
Towards Actual (Not Operational) Textual Style Transfer Auto-Evaluation—0
Wasserstein distances for evaluating cross-lingual embeddings—0
A Novel Approach for Automatic Bengali Question Answering System using Semantic Similarity Analysis—0
Textual analysis of artificial intelligence manuscripts reveals features associated with peer review outcomeCode0
A Comparison of Semantic Similarity Methods for Maximum Human Interpretability—0
Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations—0
Universal Text Representation from BERT: An Empirical Study—0
Learning Analogy-Preserving Sentence Embeddings for Answer Selection—0
Domain-Relevant Embeddings for Medical Question Similarity—0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding—0
A weakly supervised adaptive triplet loss for deep metric learning—0
Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions—0
Semantic Relatedness Based Re-ranker for Text SpottingCode0
Where are the Keys? -- Learning Object-Centric Navigation Policies on Semantic Maps with Graph Convolutional NetworksCode0
Hashtags are (not) judgemental: The untold story of Lok Sabha elections 2019—0
Emu: Enhancing Multilingual Sentence Embeddings with Semantic SpecializationCode0
Beyond BLEU: Training Neural Machine Translation with Semantic SimilarityCode0
NSURL-2019 Shared Task 8: Semantic Question Similarity in Arabic—0
SDM-Net: A Simple and Effective Model for Generalized Zero-Shot Learning—0
Unsupervised Paraphrasing by Simulated Annealing—0
Transfer Reward Learning for Policy Gradient-Based Text Generation—0
Scene Recognition with Prototype-agnostic Scene Layout—0
Specializing Unsupervised Pretraining Models for Word-Level Semantic SimilarityCode0
Do Cross Modal Systems Leverage Semantic Relationships?—0
Finding Salient Context based on Semantic Matching for Relevance Ranking—0
Term Based Semantic Clusters for Very Short Text Classification—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information—0
Push for Quantization: Deep Fisher Hashing—0
Memorizing All for Implicit Discourse Relation Recognition—0
Sentence-BERT: Sentence Embeddings using Siamese BERT-NetworksCode1
A Method for Estimating the Proximity of Vector Representation Groups in Multidimensional Space. On the Example of the Paraphrase Task—0
Phrase Localization Without Paired Training ExamplesCode0
Hamming Sentence Embeddings for Information Retrieval—0
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence EmbeddingCode0
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric—0
Interactive Variance Attention based Online Spoiler Detection for Time-Sync Comments—0
YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources—0
MSnet: A BERT-based Network for Gendered Pronoun ResolutionCode0
Specializing Distributional Vectors of All Words for Lexical Entailment—0
Context Effects on Human Judgments of Similarity—0
Annotating and analyzing the interactions between meaning relationsCode0
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
Using Thesaurus Data to Improve Coreference Resolution for Russian—0
Assessing Wordnets with WordNet EmbeddingsCode0
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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 cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT uncased (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