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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

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Showing 2251–2300 of 2381 papers

TitleStatusHype
Evaluating GenAI for Simplifying Texts for Education: Improving Accuracy and Consistency for Enhanced Readability—0
Evaluating Lexical Similarity to build Sentiment Similarity—0
Evaluating Multimodal Representations on Sentence Similarity: vSTS, Visual Semantic Textual Similarity Dataset—0
Evaluating Retrieval Augmented Generative Models for Document Queries in Transportation Safety—0
Evaluating semantic models with word-sentence relatedness—0
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric—0
Evaluating text coherence based on semantic similarity graph—0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks—0
Evaluating the Stability of Embedding-based Word Similarities—0
Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples—0
Evaluating the Utility of Model Configurations and Data Augmentation on Clinical Semantic Textual Similarity—0
Evaluating Topic Coherence Using Distributional Semantics—0
Evaluation by Association: A Systematic Study of Quantitative Word Association Evaluation—0
Evaluation Datasets for Cross-lingual Semantic Textual Similarity—0
Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Tasks—0
Evaluation of Semantic Search and its Role in Retrieved-Augmented-Generation (RAG) for Arabic Language—0
Evaluation of Simple Distributional Compositional Operations on Longer Texts—0
Evaluation of taxonomic and neural embedding methods for calculating semantic similarity—0
Evaluation on Second Language Collocational Congruency with Computational Semantic Similarity—0
EVALution 1.0: an Evolving Semantic Dataset for Training and Evaluation of Distributional Semantic Models—0
Event Detection and Co-reference with Minimal Supervision—0
Event Segmentation Applications in Large Language Model Enabled Automated Recall Assessments—0
Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data—0
EviNets: Neural Networks for Combining Evidence Signals for Factoid Question Answering—0
Evolutionary Algorithms Approach For Search Based On Semantic Document Similarity—0
Evolution of Semantic Similarity -- A Survey—0
Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-inspired Evolutionary Algorithm in the Game of Carcassonne—0
Examining Multilingual Embedding Models Cross-Lingually Through LLM-Generated Adversarial Examples—0
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks—0
ExB Themis: Extensive Feature Extraction from Word Alignments for Semantic Textual Similarity—0
Explanations for CommonsenseQA: New Dataset and Models—0
Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks—0
Explicit Retrofitting of Distributional Word Vectors—0
Exploiting Image Generality for Lexical Entailment Detection—0
Exploiting Non-Taxonomic Relations for Measuring Semantic Similarity and Relatedness in WordNet—0
Phonology-Guided Speech-to-Speech Translation for African Languages—0
ESREAL: Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models—0
Exploiting Sentence Similarities for Better Alignments—0
Exploratory topic modeling with distributional semantics—0
Exploring a Continuous and Flexible Representation of the Lexicon—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
Exploring Automatic Evaluation Methods based on a Decoder-based LLM for Text Generation—0
Exploring Content Features for Automated Speech Scoring—0
Exploring Dimensionality Reduction Techniques in Multilingual Transformers—0
Exploring Language Patterns of Prompts in Text-to-Image Generation and Their Impact on Visual Diversity—0
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games—0
Exploring Semantic Properties of Sentence Embeddings—0
Exploring Semantic Representation in Brain Activity Using Word Embeddings—0
Exploring the Correlation between Human and Machine Evaluation of Simultaneous Speech Translation—0
Exploring the effect of semantic similarity for Phrase-based Machine Translation—0
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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