Paraphrase Identification On Quora Question

评估指标

Accuracy

评测结果

各个模型在此基准测试上的表现结果

模型名称	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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