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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 71–80 of 172 papers

Title	Date	Tasks	Status	Hype
Inducing Alignment Structure with Gated Graph Attention Networks for Sentence Matching	Oct 15, 2020	Graph AttentionParaphrase Identification	—Unverified	0
Pay Attention when Required	Sep 9, 2020	Language ModellingParaphrase Identification	CodeCode Available	0
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification	Jul 22, 2020	Community Question AnsweringParaphrase Identification	—Unverified	0
Experiments on Paraphrase Identification Using Quora Question Pairs Dataset	Jun 4, 2020	Binary ClassificationParaphrase Identification	—Unverified	0
Pointwise Paraphrase Appraisal is Potentially Problematic	May 25, 2020	Binary ClassificationParaphrase Identification	—Unverified	0
Cross-Lingual Adaptation Using Universal Dependencies	Mar 24, 2020	Paraphrase IdentificationRelation Extraction	—Unverified	0
TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding	Mar 16, 2020	Machine TranslationNatural Language Inference	—Unverified	0
Matching Text with Deep Mutual Information Estimation	Mar 9, 2020	Answer SelectionMutual Information Estimation	—Unverified	0
Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems	Nov 18, 2019	intent-classificationIntent Classification	—Unverified	0
Dice Loss for Data-imbalanced NLP Tasks	Nov 7, 2019	Chinese Named Entity RecognitionMachine Reading Comprehension	CodeCode Available	0

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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