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SOTA
Semantic Textual Similarity
Semantic Textual Similarity On Sts14
Semantic Textual Similarity On Sts14
Metrics
Spearman Correlation
Results
Performance results of various models on this benchmark
Columns
Model Name
Spearman Correlation
Paper Title
AnglE-LLaMA-13B
0.8689
AnglE-optimized Text Embeddings
PromptEOL+CSE+LLaMA-30B
0.8585
Scaling Sentence Embeddings with Large Language Models
AnglE-LLaMA-7B-v2
0.8579
AnglE-optimized Text Embeddings
AnglE-LLaMA-7B
0.8549
AnglE-optimized Text Embeddings
PromptEOL+CSE+OPT-13B
0.8534
Scaling Sentence Embeddings with Large Language Models
PromptEOL+CSE+OPT-2.7B
0.8480
Scaling Sentence Embeddings with Large Language Models
PromCSE-RoBERTa-large (0.355B)
0.8381
Improved Universal Sentence Embeddings with Prompt-based Contrastive Learning and Energy-based Learning
SimCSE-RoBERTalarge
0.8236
SimCSE: Simple Contrastive Learning of Sentence Embeddings
Trans-Encoder-RoBERTa-large-cross (unsup.)
0.8194
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Trans-Encoder-RoBERTa-large-bi (unsup.)
0.8176
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Trans-Encoder-BERT-large-bi (unsup.)
0.8137
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Trans-Encoder-RoBERTa-base-cross (unsup.)
0.7903
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Trans-Encoder-BERT-base-bi (unsup.)
0.779
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
DiffCSE-BERT-base
0.7647
DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings
DiffCSE-RoBERTa-base
0.7549
DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings
SBERT-NLI-large
0.7490000000000001
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Mirror-RoBERTa-base (unsup.)
0.732
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders
Mirror-BERT-base (unsup.)
0.713
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders
Dino (STSb/̄
0.7125
Generating Datasets with Pretrained Language Models
BERTlarge-flow (target)
0.6942
On the Sentence Embeddings from Pre-trained Language Models
0 of 21 row(s) selected.
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Semantic Textual Similarity On Sts14 | SOTA | HyperAI