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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1251–1300 of 2381 papers

TitleStatusHype
RTM-DCU: Referential Translation Machines for Semantic Similarity—0
RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendation—0
RUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity by extending PMI and word embeddings systems with a Swadesh's-like list—0
Rule-based vs. Neural Net Approaches to Semantic Textual Similarity—0
RUSSE: The First Workshop on Russian Semantic Similarity—0
Saarland: Vector-based models of semantic textual similarity—0
SAARSHEFF at SemEval-2016 Task 1: Semantic Textual Similarity with Machine Translation Evaluation Metrics and (eXtreme) Boosted Tree Ensembles—0
SAGAN: An approach to Semantic Textual Similarity based on Textual Entailment—0
SAIL-GRS: Grammar Induction for Spoken Dialogue Systems using CF-IRF Rule Similarity—0
SAIL: Sentiment Analysis using Semantic Similarity and Contrast Features—0
Saliency Attention and Semantic Similarity-Driven Adversarial Perturbation—0
Saliency-Aware Regularized Graph Neural Network—0
Same Referent, Different Words: Unsupervised Mining of Opaque Coreferent Mentions—0
SAM-GAN: Self-Attention supporting Multi-stage Generative Adversarial Networks for text-to-image synthesis—0
Samsung: Align-and-Differentiate Approach to Semantic Textual Similarity—0
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity.—0
SAPPHIRE: Simple Aligner for Phrasal Paraphrase with Hierarchical Representation—0
SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression—0
Sbdlrhmn: A Rule-based Human Interpretation System for Semantic Textual Similarity Task—0
Scalable Gaussian Processes for Supervised Hashing—0
Scene-Aware Label Graph Learning for Multi-Label Image Classification—0
Scene Recognition with Prototype-agnostic Scene Layout—0
Scientific and Technological Information Oriented Semantics-adversarial and Media-adversarial Cross-media Retrieval—0
Search and Visualization of Semantically Related Words (Recherche et visualisation de mots s\'emantiquement li\'es) [in French]—0
Searching for Legal Documents at Paragraph Level: Automating Label Generation and Use of an Extended Attention Mask for Boosting Neural Models of Semantic Similarity—0
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity—0
Second-Order NLP Adversarial Examples—0
Securing from Unseen: Connected Pattern Kernels (CoPaK) for Zero-Day Intrusion Detection—0
SEEC: Semantic Vector Federation across Edge Computing Environments—0
SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding—0
Seed Words Based Data Selection for Language Model Adaptation—0
Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation—0
SEF@UHH at SemEval-2017 Task 1: Unsupervised Knowledge-Free Semantic Textual Similarity via Paragraph Vector—0
Self-Controlled Dynamic Expansion Model for Continual Learning—0
Self-Critical Alternate Learning based Semantic Broadcast Communication—0
Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss—0
SeLIP: Similarity Enhanced Contrastive Language Image Pretraining for Multi-modal Head MRI—0
*SEM 2013 shared task: Semantic Textual Similarity—0
SemAligner: A Method and Tool for Aligning Chunks with Semantic Relation Types and Semantic Similarity Scores—0
Semantic Alignment with Calibrated Similarity for Multilingual Sentence Embedding—0
Semantic Answer Similarity for Evaluating Question Answering Models—0
Semantic-based Distance Approaches in Multi-objective Genetic Programming—0
Semantic Data Set Construction from Human Clustering and Spatial Arrangement—0
Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms—0
Semantic Enhanced Few-shot Object Detection—0
Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification—0
Semantic Feature Verification in FLAN-T5—0
Semantic Information Extraction for Text Data with Probability Graph—0
Semantic Judgement of Medical Concepts: Combining Syntagmatic and Paradigmatic Information with the Tensor Encoding Model—0
Semantic Kernels for Semantic Parsing—0
Show:102550
← PrevPage 26 of 48Next →
All datasetsSTS BenchmarkMTEBMRPCSICKSTS13STS14STS12STS15STS16MRPC DevSentEvalSICK-R

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SMARTRoBERTaDev Pearson Correlation92.8—Unverified
2DeBERTa (large)Accuracy92.5—Unverified
3SMART-BERTDev Pearson Correlation90—Unverified
4MT-DNN-SMARTPearson Correlation0.93—Unverified
5StructBERTRoBERTa ensemblePearson Correlation0.93—Unverified
6Mnet-SimPearson Correlation0.93—Unverified
7XLNet (single model)Pearson Correlation0.93—Unverified
8ALBERTPearson Correlation0.93—Unverified
9T5-11BPearson Correlation0.93—Unverified
10RoBERTaPearson Correlation0.92—Unverified
#ModelMetricClaimedVerifiedStatus
1AnglE-UAESpearman Correlation84.54—Unverified
2ST5-XXLSpearman Correlation82.63—Unverified
3ST5-LargeSpearman Correlation81.83—Unverified
4ST5-XLSpearman Correlation81.66—Unverified
5ST5-BaseSpearman Correlation81.14—Unverified
6MPNet-multilingualSpearman Correlation80.73—Unverified
7SGPT-5.8B-nliSpearman Correlation80.53—Unverified
8MPNetSpearman Correlation80.28—Unverified
9MiniLM-L12Spearman Correlation79.8—Unverified
10SimCSE-BERT-supSpearman Correlation79.12—Unverified
#ModelMetricClaimedVerifiedStatus
1MT-DNN-SMARTAccuracy93.7—Unverified
2ALBERTAccuracy93.4—Unverified
3RoBERTa (ensemble)Accuracy92.3—Unverified
4BigBirdF191.5—Unverified
5StructBERTRoBERTa ensembleAccuracy91.5—Unverified
6FLOATER-largeAccuracy91.4—Unverified
7SMARTAccuracy91.3—Unverified
8RoBERTa-large 355M (MLP quantized vector-wise, fine-tuned)Accuracy91—Unverified
9RoBERTa-large 355M + Entailment as Few-shot LearnerF191—Unverified
10SpanBERTAccuracy90.9—Unverified
#ModelMetricClaimedVerifiedStatus
1PromCSE-RoBERTa-large (0.355B)Spearman Correlation0.82—Unverified
2PromptEOL+CSE+LLaMA-30BSpearman Correlation0.82—Unverified
3PromptEOL+CSE+OPT-13BSpearman Correlation0.82—Unverified
4SimCSE-RoBERTalargeSpearman Correlation0.82—Unverified
5PromptEOL+CSE+OPT-2.7BSpearman Correlation0.81—Unverified
6SentenceBERTSpearman Correlation0.75—Unverified
7SRoBERTa-NLI-baseSpearman Correlation0.74—Unverified
8SRoBERTa-NLI-largeSpearman Correlation0.74—Unverified
9Dino (STS/̄🦕)Spearman Correlation0.74—Unverified
10SBERT-NLI-largeSpearman Correlation0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1AnglE-LLaMA-7BSpearman Correlation0.91—Unverified
2AnglE-LLaMA-7B-v2Spearman Correlation0.91—Unverified
3PromptEOL+CSE+LLaMA-30BSpearman Correlation0.9—Unverified
4PromptEOL+CSE+OPT-13BSpearman Correlation0.9—Unverified
5PromptEOL+CSE+OPT-2.7BSpearman Correlation0.9—Unverified
6PromCSE-RoBERTa-large (0.355B)Spearman Correlation0.89—Unverified
7Trans-Encoder-BERT-large-bi (unsup.)Spearman Correlation0.89—Unverified
8Trans-Encoder-BERT-large-cross (unsup.)Spearman Correlation0.88—Unverified
9Trans-Encoder-RoBERTa-large-cross (unsup.)Spearman Correlation0.88—Unverified
10SimCSE-RoBERTa-largeSpearman Correlation0.87—Unverified