SOTAVerified|Agents Browse Leaderboard About

Paraphrase Identification

The goal of Paraphrase Identification is to determine whether a pair of sentences have the same meaning.

Source: Adversarial Examples with Difficult Common Words for Paraphrase Identification

Image source: On Paraphrase Identification Corpora

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 91–100 of 172 papers

Title	Date	Tasks	Status	Hype	Score
Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching	Dec 30, 2018	Information RetrievalNatural Language Inference	—Unverified	0	0
Leveraging Crowdsourcing for Paraphrase Recognition	Aug 1, 2013	Information RetrievalMachine Translation	—Unverified	0	0
LIM-LIG at SemEval-2017 Task1: Enhancing the Semantic Similarity for Arabic Sentences with Vectors Weighting	Aug 1, 2017	DescriptiveInformation Retrieval	—Unverified	0	0
LIMSIILES: Basic English Substitution for Student Answer Assessment at SemEval 2013	Jun 1, 2013	Language ModellingMachine Translation	—Unverified	0	0
Matching Natural Language Sentences with Hierarchical Sentence Factorization	Mar 1, 2018	Deep LearningParaphrase Identification	—Unverified	0	0
Matching Text with Deep Mutual Information Estimation	Mar 9, 2020	Answer SelectionMutual Information Estimation	—Unverified	0	0
Task-adaptive Pre-training and Self-training are Complementary for Natural Language Understanding	Sep 14, 2021	named-entity-recognitionNamed Entity Recognition	—Unverified	0	0
Mining Social Science Publications for Survey Variables	Aug 1, 2017	Paraphrase IdentificationQuestion Answering	—Unverified	0	0
MITRE: Seven Systems for Semantic Similarity in Tweets	Jun 1, 2015	Information RetrievalMachine Translation	—Unverified	0	0
Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce	Nov 23, 2017	ChatbotNatural Language Inference	—Unverified	0	0

Show:10 25 50

← PrevPage 10 of 18Next →

All datasets Quora Question Pairs MSRP Quora Question Pairs Dev 2017_test set AP IMDb PIT Translated SNLI Dataset in Marathi TURL WikiHop Yelp

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	BERT-Base	Direct Intrinsic Dimension	9,295	—	Unverified
2	data2vec	Accuracy	92.4	—	Unverified
3	SMART-BERT	Dev Accuracy	91.5	—	Unverified
4	ALICE	F1	90.7	—	Unverified
5	MFAE	Accuracy	90.54	—	Unverified
6	RoBERTa-large 355M + Entailment as Few-shot Learner	F1	89.2	—	Unverified
7	MwAN	Accuracy	89.12	—	Unverified
8	DIIN	Accuracy	89.06	—	Unverified
9	MSEM	Accuracy	88.86	—	Unverified
10	Bi-CAS-LSTM	Accuracy	88.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FEAT2, TFKLD, SVM, Fine-grained features	Accuracy	80.41	—	Unverified
2	NMF factorization-unigrams-TFKLD	Accuracy	72.75	—	Unverified
3	SWEM-concat	Accuracy	71.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT + SCH attm	Val Accuracy	91.42	—	Unverified
2	BERT + SCH attn	Val F1 Score	88.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	10 fold Cross validation	50	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBETRa base	MCC	0.53	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SplitEE-S	Accuracy	82.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TSDAE	AP	69.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Weighted Ensemble of TF-IDF and BERT Embeddings	1:1 Accuracy	82.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TSDAE	AP	76.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	StructBERTRoBERTa ensemble	Accuracy	90.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SplitEE-S	Accuracy	76.7	—	Unverified