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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 1501–1550 of 2381 papers

TitleStatusHype
IRIT: Textual Similarity Combining Conceptual Similarity with an N-Gram Comparison Method—0
ISCAS\_NLP at SemEval-2016 Task 1: Sentence Similarity Based on Support Vector Regression using Multiple Features—0
Is Contrasting All You Need? Contrastive Learning for the Detection and Attribution of AI-generated Text—0
Is Cosine-Similarity of Embeddings Really About Similarity?—0
Isolating authorship from content with semantic embeddings and contrastive learning—0
Is this a Child, a Girl or a Car? Exploring the Contribution of Distributional Similarity to Learning Referential Word Meanings—0
Is Twitter A Better Corpus for Measuring Sentiment Similarity?—0
Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match—0
ITNLP-AiKF at SemEval-2016 Task 3 a quesiton answering system using community QA repository—0
ITNLP-AiKF at SemEval-2017 Task 1: Rich Features Based SVR for Semantic Textual Similarity Computing—0
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention—0
It's About Time: Incorporating Temporality in Retrieval Augmented Language Models—0
iUBC at SemEval-2016 Task 2: RNNs and LSTMs for interpretable STS—0
JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets—0
Jailbreaking the Text-to-Video Generative Models—0
JAMES: Normalizing Job Titles with Multi-Aspect Graph Embeddings and Reasoning—0
janardhan: Semantic Textual Similarity using Universal Networking Language graph matching—0
jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images—0
Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models—0
Joint Learning of Distributed Representations for Images and Texts—0
JU\_CSE\_NLP: Multi-grade Classification of Semantic Similarity between Text Pairs—0
JU-Evora: A Graph Based Cross-Level Semantic Similarity Analysis using Discourse Information—0
JUNITMZ at SemEval-2016 Task 1: Identifying Semantic Similarity Using Levenshtein Ratio—0
Just an Update on PMING Distance for Web-based Semantic Similarity in Artificial Intelligence and Data Mining—0
Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text—0
KEViN: A Knowledge Enhanced Validity and Novelty Classifier for Arguments—0
KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment—0
KIT-Multi: A Translation-Oriented Multilingual Embedding Corpus—0
KLUE-CORE: A regression model of semantic textual similarity—0
KnCe2013-CORE:Semantic Text Similarity by use of Knowledge Bases—0
KNNs of Semantic Encodings for Rating Prediction—0
Knowing the Author by the Company His Words Keep—0
Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach—0
Enhancing Unsupervised Sentence Embeddings via Knowledge-Driven Data Augmentation and Gaussian-Decayed Contrastive Learning—0
Knowledge Base Unification via Sense Embeddings and Disambiguation—0
Knowledge Graph Construction and Its Application in Automatic Radiology Report Generation from Radiologist's Dictation—0
Knowledge Graph Fusion for Language Model Fine-tuning—0
Knowledge Tagging System on Math Questions via LLMs with Flexible Demonstration Retriever—0
Know When To Stop: A Study of Semantic Drift in Text Generation—0
KVShare: An LLM Service System with Efficient and Effective Multi-Tenant KV Cache Reuse—0
L2F/INESC-ID at SemEval-2017 Tasks 1 and 2: Lexical and semantic features in word and textual similarity—0
Label-anticipated Event Disentanglement for Audio-Visual Video Parsing—0
Language-agnostic, automated assessment of listeners' speech recall using large language models—0
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction—0
Language-Informed Transfer Learning for Embodied Household Activities—0
Language Models Explain Word Reading Times Better Than Empirical Predictability—0
Language Specific Knowledge: Do Models Know Better in X than in English?—0
Language Transfer Learning for Supervised Lexical Substitution—0
LanguaShrink: Reducing Token Overhead with Psycholinguistics—0
Large Language Model Augmented Exercise Retrieval for Personalized Language Learning—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