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 851–900 of 2381 papers

TitleStatusHype
CLaC-CORE: Exhaustive Feature Combination for Measuring Textual Similarity—0
Extending Monolingual Semantic Textual Similarity Task to Multiple Cross-lingual Settings—0
Extending WordNet with Fine-Grained Collocational Information via Supervised Distributional Learning—0
Extracting Sentence Embeddings from Pretrained Transformer Models—0
Extrapolating Binder Style Word Embeddings to New Words—0
FacTeR-Check: Semi-automated fact-checking through Semantic Similarity and Natural Language Inference—0
Exploiting Sentence Similarities for Better Alignments—0
ASAP-II: From the Alignment of Phrases to Textual Similarity—0
ESREAL: Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models—0
CIMON: Towards High-quality Hash Codes—0
FaMTEB: Massive Text Embedding Benchmark in Persian Language—0
FarFetched: An Entity-centric Approach for Reasoning on Textually Represented Environments—0
Phonology-Guided Speech-to-Speech Translation for African Languages—0
Exploiting Non-Taxonomic Relations for Measuring Semantic Similarity and Relatedness in WordNet—0
CICBUAPnlp: Graph-Based Approach for Answer Selection in Community Question Answering Task—0
A Robust Approach to Aligning Heterogeneous Lexical Resources—0
ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes—0
Exploiting Image Generality for Lexical Entailment Detection—0
Explicit Retrofitting of Distributional Word Vectors—0
FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting—0
Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks—0
FBK-HLT: An Application of Semantic Textual Similarity for Answer Selection in Community Question Answering—0
FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter—0
FBK-HLT: A New Framework for Semantic Textual Similarity—0
Explanations for CommonsenseQA: New Dataset and Models—0
FBK-HLT-NLP at SemEval-2016 Task 2: A Multitask, Deep Learning Approach for Interpretable Semantic Textual Similarity—0
FBK: Machine Translation Evaluation and Word Similarity metrics for Semantic Textual Similarity—0
FBK-TR: Applying SVM with Multiple Linguistic Features for Cross-Level Semantic Similarity—0
Check-Eval: A Checklist-based Approach for Evaluating Text Quality—0
FCICU at SemEval-2017 Task 1: Sense-Based Language Independent Semantic Textual Similarity Approach—0
ExB Themis: Extensive Feature Extraction from Word Alignments for Semantic Textual Similarity—0
Feature Engineering in Learning-to-Rank for Community Question Answering Task—0
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models—0
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks—0
Chasing Hypernyms in Vector Spaces with Entropy—0
Feedforward Legendre Memory Unit—0
Argument extraction for supporting public policy formulation—0
A corpus-based evaluation method for Distributional Semantic Models—0
Examining Multilingual Embedding Models Cross-Lingually Through LLM-Generated Adversarial Examples—0
Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-inspired Evolutionary Algorithm in the Game of Carcassonne—0
Evolution of Semantic Similarity -- A Survey—0
Few-shot Named Entity Recognition with Joint Token and Sentence Awareness—0
Evolutionary Algorithms Approach For Search Based On Semantic Document Similarity—0
Characters or Morphemes: How to Represent Words?—0
EviNets: Neural Networks for Combining Evidence Signals for Factoid Question Answering—0
FILM: A Fast, Interpretable, and Low-rank Metric Learning Approach for Sentence Matching—0
Filter and Match Approach to Pair-wise Web URI Linking—0
Finding Salient Context based on Semantic Matching for Relevance Ranking—0
Finding the Topic of a Set of Images—0
Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data—0
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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