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 21012150 of 2381 papers

TitleStatusHype
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction TasksCode0
Short Text Hashing Improved by Integrating Multi-Granularity Topics and TagsCode0
Auto-Encoding Dictionary Definitions into Consistent Word EmbeddingsCode0
Glyce: Glyph-vectors for Chinese Character RepresentationsCode0
Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question AnsweringCode0
Temporal and Semantic Evaluation Metrics for Foundation Models in Post-Hoc Analysis of Robotic Sub-tasksCode0
CitRet: A Hybrid Model for Cited Text Span RetrievalCode0
Global and Local Information Adjustment for Semantic Similarity EvaluationCode0
Neural sentence embedding models for semantic similarity estimation in the biomedical domainCode0
Supervised Online Hashing via Hadamard Codebook LearningCode0
Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence GenerationCode0
Term Expansion and FinBERT fine-tuning for Hypernym and Synonym Ranking of Financial TermsCode0
Investigating semantic subspaces of Transformer sentence embeddings through linear structural probingCode0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Adversarial Self-Attention for Language UnderstandingCode0
Transfer Fine-Tuning: A BERT Case StudyCode0
Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental HealthCode0
GiBERT: Enhancing BERT with Linguistic Information using a Lightweight Gated Injection MethodCode0
Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning ModelsCode0
TextBugger: Generating Adversarial Text Against Real-world ApplicationsCode0
Sim-GPT: Text Similarity via GPT Annotated DataCode0
NLP Verification: Towards a General Methodology for Certifying RobustnessCode0
Saliency Suppressed, Semantics Surfaced: Visual Transformations in Neural Networks and the BrainCode0
Does the Objective Matter? Comparing Training Objectives for Pronoun ResolutionCode0
Transfer learning for semantic similarity measures based on symbolic regressionCode0
Distilling Word Meaning in Context from Pre-trained Language ModelsCode0
Distilling the Knowledge of Romanian BERTs Using Multiple TeachersCode0
You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LMCode0
SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt DenoisingCode0
Chinese Word Sense Embedding with SememeWSD and Synonym SetCode0
Novel Categories Discovery Via Constraints on Empirical Prediction StatisticsCode0
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring TasksCode0
Asymmetric Visual Semantic Embedding Framework for Efficient Vision-Language AlignmentCode0
Check_square at CheckThat! 2020: Claim Detection in Social Media via Fusion of Transformer and Syntactic FeaturesCode0
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its ApplicationsCode0
Character-based Neural Networks for Sentence Pair ModelingCode0
TransFool: An Adversarial Attack against Neural Machine Translation ModelsCode0
Jmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarityCode0
Utilizing a null class to restrict decision spaces and defend against neural network adversarial attacksCode0
Joint Word Representation Learning using a Corpus and a Semantic LexiconCode0
Utilizing Semantic Textual Similarity for Clinical Survey Data Feature SelectionCode0
Distilling Monolingual and Crosslingual Word-in-Context RepresentationsCode0
Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMsCode0
Assessing Wordnets with WordNet EmbeddingsCode0
GenSense: A Generalized Sense Retrofitting ModelCode0
Category-aware EEG image generation based on wavelet transform and contrast semantic lossCode0
Generating Natural Language Adversarial Examples through Probability Weighted Word SaliencyCode0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
Generating More Interesting Responses in Neural Conversation Models with Distributional ConstraintsCode0
REINFOREST: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search ModelsCode0
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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