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Linguistic Acceptability

Linguistic Acceptability is the task of determining whether a sentence is grammatical or ungrammatical.

Image Source: Warstadt et al

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 41–50 of 72 papers

Title	Date	Tasks	Status	Hype
Not all layers are equally as important: Every Layer Counts BERT	Nov 3, 2023	AllLinguistic Acceptability	—Unverified	0
CLEAR: Contrastive Learning for Sentence Representation	Dec 31, 2020	Contrastive LearningLinguistic Acceptability	—Unverified	0
Cross-Architecture Distillation Using Bidirectional CMOW Embeddings	Sep 29, 2021	Linguistic AcceptabilityQQP	—Unverified	0
DaLAJ - a dataset for linguistic acceptability judgments for Swedish: Format, baseline, sharing	May 14, 2021	Binary ClassificationLinguistic Acceptability	—Unverified	0
DaLAJ – a dataset for linguistic acceptability judgments for Swedish	May 1, 2021	Linguistic Acceptability	—Unverified	0
Data-Free Distillation of Language Model by Text-to-Text Transfer	Nov 3, 2023	Data-free Knowledge DistillationDiversity	—Unverified	0
Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection	Jul 31, 2023	Adversarial AttackInformation Retrieval	—Unverified	0
Dissecting Bias in LLMs: A Mechanistic Interpretability Perspective	Jun 5, 2025	Linguistic Acceptabilitynamed-entity-recognition	—Unverified	0
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT	Sep 12, 2019	Linguistic AcceptabilityNatural Language Inference	—Unverified	0
Rating Distributions and Bayesian Inference: Enhancing Cognitive Models of Spatial Language Use	Jul 1, 2018	Bayesian InferenceLinguistic Acceptability	—Unverified	0

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All datasets CoLA RuCoLA CoLA Dev ItaCoLA DaLAJ

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	En-BERT + TDA + PCA	Accuracy	88.6	—	Unverified
2	BERT+TDA	Accuracy	88.2	—	Unverified
3	RoBERTa+TDA	Accuracy	87.3	—	Unverified
4	deberta-v3-base+tasksource	Accuracy	87.15	—	Unverified
5	RoBERTa-large 355M + Entailment as Few-shot Learner	Accuracy	86.4	—	Unverified
6	LTG-BERT-base 98M	Accuracy	82.7	—	Unverified
7	ELC-BERT-base 98M	Accuracy	82.6	—	Unverified
8	En-BERT + TDA	Accuracy	82.1	—	Unverified
9	FNet-Large	Accuracy	78	—	Unverified
10	LTG-BERT-small 24M	Accuracy	77.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Ru-RoBERTa+TDA	MCC	0.59	—	Unverified
2	ruRoBERTa	MCC	0.53	—	Unverified
3	Ru-BERT+TDA	MCC	0.48	—	Unverified
4	RemBERT	MCC	0.44	—	Unverified
5	ruBERT	MCC	0.42	—	Unverified
6	ruGPT-3	MCC	0.3	—	Unverified
7	ruT5	MCC	0.25	—	Unverified
8	mBERT	MCC	0.15	—	Unverified
9	XLM-R	MCC	0.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	En-BERT + TDA	Accuracy	88.6	—	Unverified
2	XLM-R (pre-trained) + TDA	Accuracy	73	—	Unverified
3	DeBERTa (large)	Accuracy	69.5	—	Unverified
4	TinyBERT-6 67M	Accuracy	54	—	Unverified
5	Synthesizer (R+V)	Accuracy	53.3	—	Unverified
6	En-BERT (pre-trained) + TDA	MCC	0.42	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	XLM-R + TDA	MCC	0.68	—	Unverified
2	XLM-R	MCC	0.52	—	Unverified
3	It-BERT (pre-trained) + TDA	MCC	0.48	—	Unverified
4	mBERT	MCC	0.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Sw-BERT + H0M	Accuracy	76.9	—	Unverified