Paraphrase Identification On Quora Question

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name	Accuracy	Paper Title	Repository
MwAN	89.12	Multiway Attention Networks for Modeling Sentence Pairs
XLNet-Large (ensemble)	90.3	XLNet: Generalized Autoregressive Pretraining for Language Understanding	-
RoBERTa-large 355M + Entailment as Few-shot Learner	-	Entailment as Few-Shot Learner	-
ERNIE	-	ERNIE: Enhanced Language Representation with Informative Entities	-
ASA + BERT-base	-	Adversarial Self-Attention for Language Understanding	-
TRANS-BLSTM	88.28	TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding	-
RealFormer	91.34	RealFormer: Transformer Likes Residual Attention	-
SplitEE-S	-	SplitEE: Early Exit in Deep Neural Networks with Split Computing	-
SMART-BERT	-	SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization	-
MT-DNN	89.6	Multi-Task Deep Neural Networks for Natural Language Understanding	-
GenSen	87.01	Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning	-
ASA + RoBERTa	-	Adversarial Self-Attention for Language Understanding	-
DIIN	89.06	Natural Language Inference over Interaction Space	-
FNet-Large	-	FNet: Mixing Tokens with Fourier Transforms	-
1-3[0.8pt/2pt] Random	80	Self-Explaining Structures Improve NLP Models	-
StructBERTRoBERTa ensemble	90.7	StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding	-
BERT-Base	-	Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning	-
BiMPM	88.17	Bilateral Multi-Perspective Matching for Natural Language Sentences	-
FreeLB	74.8	SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization	-
BERT-LARGE	-	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	-

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