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
RTM-DCU: Referential Translation Machines for Semantic Similarity0
ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment0
ECNU: Leveraging on Ensemble of Heterogeneous Features and Information Enrichment for Cross Level Semantic Similarity Estimation0
SimCompass: Using Deep Learning Word Embeddings to Assess Cross-level Similarity0
Duluth : Measuring Cross-Level Semantic Similarity with First and Second Order Dictionary Overlaps0
Compositional Distributional Semantics Models in Chunk-based Smoothed Tree Kernels0
SSMT:A Machine Translation Evaluation View To Paragraph-to-Sentence Semantic Similarity0
Illinois-LH: A Denotational and Distributional Approach to Semantics0
Contrasting Syntagmatic and Paradigmatic Relations: Insights from Distributional Semantic Models0
FBK-TR: Applying SVM with Multiple Linguistic Features for Cross-Level Semantic Similarity0
OPI: Semeval-2014 Task 3 System Description0
Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor0
DLS@CU: Sentence Similarity from Word Alignment0
UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual EntailmentCode0
NTNU: Measuring Semantic Similarity with Sublexical Feature Representations and Soft Cardinality0
TCDSCSS: Dimensionality Reduction to Evaluate Texts of Varying Lengths - an IR Approach0
UoW: Multi-task Learning Gaussian Process for Semantic Textual Similarity0
TeamZ: Measuring Semantic Textual Similarity for Spanish Using an Overlap-Based Approach0
HulTech: A General Purpose System for Cross-Level Semantic Similarity based on Anchor Web Counts0
The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity0
DIT: Summarisation and Semantic Expansion in Evaluating Semantic Similarity0
UNIBA: Combining Distributional Semantic Models and Word Sense Disambiguation for Textual Similarity0
An analysis of textual inference in German customer emails0
Meerkat Mafia: Multilingual and Cross-Level Semantic Textual Similarity Systems0
tucSage: Grammar Rule Induction for Spoken Dialogue Systems via Probabilistic Candidate Selection0
AI-KU: Using Co-Occurrence Modeling for Semantic Similarity0
UMCC\_DLSI\_SemSim: Multilingual System for Measuring Semantic Textual Similarity0
UNAL-NLP: Combining Soft Cardinality Features for Semantic Textual Similarity, Relatedness and Entailment0
LIPN: Introducing a new Geographical Context Similarity Measure and a Statistical Similarity Measure based on the Bhattacharyya coefficient0
Using a generic neural model for lexical substitution (Utiliser un mod\`ele neuronal g\'en\'erique pour la substitution lexicale) [in French]0
Resolving the Representational Problems of Polarity and Interaction between Process and State Verbs0
Target-Centric Features for Translation Quality Estimation0
Structuring Operative Notes using Active Learning0
Detecting linguistic idiosyncratic interests in autism using distributional semantic models0
Using Ellipsis Detection and Word Similarity for Transformation of Spoken Language into Grammatically Valid Sentences0
Referential Translation Machines for Predicting Translation Quality0
Metaphor Detection through Term Relevance0
Multi-dimensional abstractness in cross-domain mappings0
Probabilistic Modeling of Joint-context in Distributional Similarity0
Product Feature Mining: Semantic Clues versus Syntactic Constituents0
Learning to Predict Distributions of Words Across Domains0
Modeling Prompt Adherence in Student Essays0
Semantic Parsing for Single-Relation Question Answering0
Distributed Representations of Geographically Situated Language0
A Robust Approach to Aligning Heterogeneous Lexical Resources0
Predicting the relevance of distributional semantic similarity with contextual information0
Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction0
Vector spaces for historical linguistics: Using distributional semantics to study syntactic productivity in diachrony0
Depeche Mood: a Lexicon for Emotion Analysis from Crowd Annotated News0
Bilingually-constrained Phrase Embeddings for Machine Translation0
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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