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

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Showing 101–125 of 172 papers

Title	Date	Tasks	Status
A Unified Kernel Approach for Learning Typed Sentence Rewritings	Jul 1, 2015	Machine TranslationNatural Language Inference	—Unverified
The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification	Oct 1, 2018	ClusteringParaphrase Identification	—Unverified
MultiGranCNN: An Architecture for General Matching of Text Chunks on Multiple Levels of Granularity	Jul 1, 2015	Machine TranslationParaphrase Identification	—Unverified
Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks	Sep 1, 2015	Feature EngineeringMachine Translation	—Unverified
Multiresolution Graph Attention Networks for Relevance Matching	Feb 27, 2019	Graph AttentionInformation Retrieval	—Unverified
UMCC\_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance	Jun 1, 2013	Information RetrievalParaphrase Identification	—Unverified
Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems	Nov 18, 2019	intent-classificationIntent Classification	—Unverified
Unsupervised Paraphrasing without Translation	May 29, 2019	Machine TranslationParaphrase Identification	—Unverified
Towards Automatic Short Answer Assessment for Finnish as a Paraphrase Retrieval Task	Jul 1, 2022	Paraphrase IdentificationRetrieval	—Unverified
UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports	Jun 1, 2016	Information RetrievalLanguage Modeling	—Unverified
Neural Paraphrase Identification of Questions with Noisy Pretraining	Apr 15, 2017	Paraphrase Identification	—Unverified
Assessing the Eligibility of Backtranslated Samples Based on Semantic Similarity for the Paraphrase Identification Task	Sep 1, 2021	MRPCParaphrase Identification	—Unverified
On Paraphrase Identification Corpora	May 1, 2014	DiversityNatural Language Inference	—Unverified
Original Semantics-Oriented Attention and Deep Fusion Network for Sentence Matching	Nov 1, 2019	Natural Language InferenceParaphrase Identification	—Unverified
ASOBEK at SemEval-2016 Task 1: Sentence Representation with Character N-gram Embeddings for Semantic Textual Similarity	Jun 1, 2016	Language ModelingLanguage Modelling	—Unverified
Paraphrase Identification and Semantic Similarity in Twitter with Simple Features	Jun 1, 2015	Information RetrievalMachine Translation	—Unverified
Paraphrase Identification with Deep Learning: A Review of Datasets and Methods	Dec 13, 2022	Paraphrase IdentificationText Generation	—Unverified
A Continuously Growing Dataset of Sentential Paraphrases	Aug 1, 2017	BenchmarkingParaphrase Identification	—Unverified
Paraphrasing, textual entailment, and semantic similarity above word level	Aug 10, 2022	Natural Language InferenceParaphrase Identification	—Unverified
Towards Domain-Generalizable Paraphrase Identification by Avoiding the Shortcut Learning	Sep 1, 2021	Domain GeneralizationParaphrase Identification	—Unverified
A Qualitative Evaluation Framework for Paraphrase Identification	Sep 1, 2019	Paraphrase Identification	—Unverified
Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoders	Oct 11, 2022	Paraphrase IdentificationSensitivity	—Unverified
PerPaDa: A Persian Paraphrase Dataset based on Implicit Crowdsourcing Data Collection	Jan 17, 2022	Paraphrase Identification	—Unverified
Pointwise Paraphrase Appraisal is Potentially Problematic	May 25, 2020	Binary ClassificationParaphrase Identification	—Unverified
Predicate-Argument Based Bi-Encoder for Paraphrase Identification	Nov 16, 2021	Paraphrase IdentificationSentence	—Unverified

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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