SOTAVerified

Semantic Textual Similarity

Semantic textual similarity deals with determining how similar two pieces of texts are. This can take the form of assigning a score from 1 to 5. Related tasks are paraphrase or duplicate identification.

Image source: Learning Semantic Textual Similarity from Conversations

Papers

Showing 14511500 of 2381 papers

TitleStatusHype
Temporal Analysis of Entity Relatedness and its Evolution using Wikipedia and DBpedia0
A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions0
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsCode0
MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs0
Twitter-based traffic information system based on vector representations for words0
Learning semantic similarity in a continuous space0
Generative Models for Simulating Mobility Trajectories0
The MeSH-gram Neural Network Model: Extending Word Embedding Vectors with MeSH Concepts for UMLS Semantic Similarity and Relatedness in the Biomedical Domain0
Sequence Learning with RNNs for Medical Concept Normalization in User-Generated Texts0
Generalised Differential Privacy for Text Document Processing0
Not just a matter of semantics: the relationship between visual similarity and semantic similarity0
Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Automated Fact-Checking of Claims in Argumentative Parliamentary Debates0
Neural sentence generation from formal semantics0
MindLab Neural Network Approach at BioASQ 6B0
Efficient learning of neighbor representations for boundary trees and forests0
Predicting the Semantic Textual Similarity with Siamese CNN and LSTM0
A mathematical theory of semantic development in deep neural networksCode0
Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks0
Improving Multilingual Semantic Textual Similarity with Shared Sentence Encoder for Low-resource Languages0
Training Complex Models with Multi-Task Weak SupervisionCode0
Dynamics and Reachability of Learning Tasks0
A Graph-theoretic Summary Evaluation for ROUGE0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations0
Supervised Clustering of Questions into Intents for Dialog System Applications0
Encoding Gated Translation Memory into Neural Machine Translation0
Auto-Encoding Dictionary Definitions into Consistent Word EmbeddingsCode0
The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification0
Automatic Pyramid Evaluation Exploiting EDU-based Extractive Reference Summaries0
Increasing In-Class Similarity by Retrofitting Embeddings with Demographic InformationCode0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data0
Accurate semantic textual similarity for cleaning noisy parallel corpora using semantic machine translation evaluation metric: The NRC supervised submissions to the Parallel Corpus Filtering task0
Controlling Length in Abstractive Summarization Using a Convolutional Neural NetworkCode0
Hierarchy-based Image Embeddings for Semantic Image RetrievalCode0
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA0
Evaluating Multimodal Representations on Sentence Similarity: vSTS, Visual Semantic Textual Similarity Dataset0
Generating More Interesting Responses in Neural Conversation Models with Distributional ConstraintsCode0
Hypernyms Through Intra-Article Organization in Wikipedia0
Semi-Supervised Generative Adversarial Hashing for Image Retrieval0
Xu: An Automated Query Expansion and Optimization Tool0
Learning Graph Embeddings from WordNet-based Similarity Measures0
Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia ContentCode0
A Joint Sequence Fusion Model for Video Question Answering and RetrievalCode0
An Efficient Approach to Learning Chinese Judgment Document Similarity Based on Knowledge Summarization0
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activationsCode0
Rule-based vs. Neural Net Approaches to Semantic Textual Similarity0
Recognizing Humour using Word Associations and Humour Anchor Extraction0
Convolutional Neural Network for Universal Sentence Embeddings0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SMARTRoBERTaDev Pearson Correlation92.8Unverified
2DeBERTa (large)Accuracy92.5Unverified
3SMART-BERTDev Pearson Correlation90Unverified
4MT-DNN-SMARTPearson Correlation0.93Unverified
5StructBERTRoBERTa ensemblePearson Correlation0.93Unverified
6Mnet-SimPearson Correlation0.93Unverified
7XLNet (single model)Pearson Correlation0.93Unverified
8ALBERTPearson Correlation0.93Unverified
9T5-11BPearson Correlation0.93Unverified
10RoBERTaPearson Correlation0.92Unverified
#ModelMetricClaimedVerifiedStatus
1AnglE-UAESpearman Correlation84.54Unverified
2ST5-XXLSpearman Correlation82.63Unverified
3ST5-LargeSpearman Correlation81.83Unverified
4ST5-XLSpearman Correlation81.66Unverified
5ST5-BaseSpearman Correlation81.14Unverified
6MPNet-multilingualSpearman Correlation80.73Unverified
7SGPT-5.8B-nliSpearman Correlation80.53Unverified
8MPNetSpearman Correlation80.28Unverified
9MiniLM-L12Spearman Correlation79.8Unverified
10SimCSE-BERT-supSpearman Correlation79.12Unverified
#ModelMetricClaimedVerifiedStatus
1MT-DNN-SMARTAccuracy93.7Unverified
2ALBERTAccuracy93.4Unverified
3RoBERTa (ensemble)Accuracy92.3Unverified
4BigBirdF191.5Unverified
5StructBERTRoBERTa ensembleAccuracy91.5Unverified
6FLOATER-largeAccuracy91.4Unverified
7SMARTAccuracy91.3Unverified
8RoBERTa-large 355M (MLP quantized vector-wise, fine-tuned)Accuracy91Unverified
9RoBERTa-large 355M + Entailment as Few-shot LearnerF191Unverified
10SpanBERTAccuracy90.9Unverified
#ModelMetricClaimedVerifiedStatus
1PromCSE-RoBERTa-large (0.355B)Spearman Correlation0.82Unverified
2PromptEOL+CSE+LLaMA-30BSpearman Correlation0.82Unverified
3PromptEOL+CSE+OPT-13BSpearman Correlation0.82Unverified
4SimCSE-RoBERTalargeSpearman Correlation0.82Unverified
5PromptEOL+CSE+OPT-2.7BSpearman Correlation0.81Unverified
6SentenceBERTSpearman Correlation0.75Unverified
7SRoBERTa-NLI-baseSpearman Correlation0.74Unverified
8SRoBERTa-NLI-largeSpearman Correlation0.74Unverified
9Dino (STS/̄🦕)Spearman Correlation0.74Unverified
10SBERT-NLI-largeSpearman Correlation0.74Unverified
#ModelMetricClaimedVerifiedStatus
1AnglE-LLaMA-7BSpearman Correlation0.91Unverified
2AnglE-LLaMA-7B-v2Spearman Correlation0.91Unverified
3PromptEOL+CSE+LLaMA-30BSpearman Correlation0.9Unverified
4PromptEOL+CSE+OPT-13BSpearman Correlation0.9Unverified
5PromptEOL+CSE+OPT-2.7BSpearman Correlation0.9Unverified
6PromCSE-RoBERTa-large (0.355B)Spearman Correlation0.89Unverified
7Trans-Encoder-BERT-large-bi (unsup.)Spearman Correlation0.89Unverified
8Trans-Encoder-BERT-large-cross (unsup.)Spearman Correlation0.88Unverified
9Trans-Encoder-RoBERTa-large-cross (unsup.)Spearman Correlation0.88Unverified
10SimCSE-RoBERTa-largeSpearman Correlation0.87Unverified