SOTAVerified|Agents Browse Leaderboard About

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 1–10 of 72 papers

Title	Date	Tasks	Status	Hype
Dissecting Bias in LLMs: A Mechanistic Interpretability Perspective	Jun 5, 2025	Linguistic Acceptabilitynamed-entity-recognition	—Unverified	0
Fietje: An open, efficient LLM for Dutch	Dec 19, 2024	Linguistic AcceptabilitySentiment Analysis	CodeCode Available	2
Robust ASR Error Correction with Conservative Data Filtering	Jul 18, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Learning Phonotactics from Linguistic Informants	May 8, 2024	Linguistic Acceptability	—Unverified	0
MELA: Multilingual Evaluation of Linguistic Acceptability	Nov 15, 2023	Code GenerationCross-Lingual Transfer	CodeCode Available	0
Not all layers are equally as important: Every Layer Counts BERT	Nov 3, 2023	AllLinguistic Acceptability	—Unverified	0
Data-Free Distillation of Language Model by Text-to-Text Transfer	Nov 3, 2023	Data-free Knowledge DistillationDiversity	—Unverified	0
How well can machine-generated texts be identified and can language models be trained to avoid identification?	Oct 25, 2023	Linguistic AcceptabilityText Generation	—Unverified	0
JCoLA: Japanese Corpus of Linguistic Acceptability	Sep 22, 2023	ArticlesLinguistic Acceptability	CodeCode Available	1
Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection	Jul 31, 2023	Adversarial AttackInformation Retrieval	—Unverified	0

Show:10 25 50

← PrevPage 1 of 8Next →

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