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SOTA
Semantic Textual Similarity
Semantic Textual Similarity On Sick
Semantic Textual Similarity On Sick
Metrics
Spearman Correlation
Results
Performance results of various models on this benchmark
Columns
Model Name
Spearman Correlation
Paper Title
Repository
Trans-Encoder-BERT-large-bi (unsup.)
0.7133
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Mirror-RoBERTa-base (unsup.)
0.706
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders
SRoBERTa-NLI-large
0.7429
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Trans-Encoder-RoBERTa-large-cross (unsup.)
0.7163
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
SimCSE-RoBERTalarge
0.8195
SimCSE: Simple Contrastive Learning of Sentence Embeddings
SRoBERTa-NLI-base
0.7446
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Dino (STSb/̄
0.6809
Generating Datasets with Pretrained Language Models
PromCSE-RoBERTa-large (0.355B)
0.8243
Improved Universal Sentence Embeddings with Prompt-based Contrastive Learning and Energy-based Learning
Trans-Encoder-BERT-base-cross (unsup.)
0.6952
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Rematch
0.6772
Rematch: Robust and Efficient Matching of Local Knowledge Graphs to Improve Structural and Semantic Similarity
SBERT-NLI-base
0.7291
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
SBERT-NLI-large
0.7375
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
IS-BERT-NLI
0.6425
An Unsupervised Sentence Embedding Method by Mutual Information Maximization
Dino (STS/̄
0.7426
Generating Datasets with Pretrained Language Models
PromptEOL+CSE+OPT-13B
0.8206
Scaling Sentence Embeddings with Large Language Models
PromptEOL+CSE+OPT-2.7B
0.8129
Scaling Sentence Embeddings with Large Language Models
Mirror-BERT-base (unsup.)
0.703
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders
BERTbase-flow (NLI)
0.6544
On the Sentence Embeddings from Pre-trained Language Models
-
SentenceBERT
0.7462
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Trans-Encoder-BERT-base-bi (unsup.)
0.7276
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
0 of 22 row(s) selected.
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