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 651700 of 2381 papers

TitleStatusHype
Beyond Word2Vec: Embedding Words and Phrases in Same Vector SpaceCode0
EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via Action PruningCode0
Estimating Semantic Similarity between In-Domain and Out-of-Domain SamplesCode0
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measuresCode0
Exploiting Semantic Role Contextualized Video Features for Multi-Instance Text-Video Retrieval EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022Code0
Modelling Sentence Pairs with Tree-structured Attentive EncoderCode0
A Comparative Study of Text Embedding Models for Semantic Text Similarity in Bug ReportsCode0
MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations PredictionCode0
Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental HealthCode0
Counter-fitting Word Vectors to Linguistic ConstraintsCode0
SueNes: A Weakly Supervised Approach to Evaluating Single-Document Summarization via Negative SamplingCode0
Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource LanguagesCode0
Emu: Enhancing Multilingual Sentence Embeddings with Semantic SpecializationCode0
Multi-stage Distillation Framework for Cross-Lingual Semantic Similarity MatchingCode0
A Generalized Method for Automated Multilingual Loanword DetectionCode0
Near-lossless Binarization of Word EmbeddingsCode0
A character-based steganography using masked language modelingCode0
Correlations between Word Vector SetsCode0
Correlation Coefficients and Semantic Textual SimilarityCode0
Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question AnsweringCode0
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring TasksCode0
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence RepresentationsCode0
Correcting ContradictionsCode0
Embeddings Evaluation Using a Novel Measure of Semantic SimilarityCode0
Novel Categories Discovery Via Constraints on Empirical Prediction StatisticsCode0
EL Embeddings: Geometric construction of models for the Description Logic EL ++Code0
Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal ReasoningCode0
COPER: a Query-adaptable Semantics-based Search Engine for Persian COVID-19 ArticlesCode0
Efficient Heuristics Generation for Solving Combinatorial Optimization Problems Using Large Language ModelsCode0
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word VectorsCode0
EMBEDDIA at SemEval-2022 Task 8: Investigating Sentence, Image, and Knowledge Graph Representations for Multilingual News Article SimilarityCode0
Entity-enhanced Adaptive Reconstruction Network for Weakly Supervised Referring Expression GroundingCode0
FAT ALBERT: Finding Answers in Large Texts using Semantic Similarity Attention Layer based on BERTCode0
Hybrid Semantic Recommender System for Chemical CompoundsCode0
Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer0
Convolutional Neural Network for Universal Sentence Embeddings0
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models0
Attention Discriminant Sampling for Point Clouds0
A Multilingual Dataset for Evaluating Parallel Sentence Extraction from Comparable Corpora0
Contrastive Word Embedding Learning for Neural Machine Translation0
Attention-based Cross-Layer Domain Alignment for Unsupervised Domain Adaptation0
Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations0
Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder0
Attention-aware semantic relevance predicting Chinese sentence reading0
A Multi-level Alignment Training Scheme for Video-and-Language Grounding0
A Deep Decomposable Model for Disentangling Syntax and Semantics in Sentence Representation0
Contrastive Learning Subspace for Text Clustering0
Contrastive Learning of Sentence Representations0
A Thesaurus for Biblical Hebrew0
AMRITA\_CEN@SemEval-2015: Paraphrase Detection for Twitter using Unsupervised Feature Learning with Recursive Autoencoders0
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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