Natural Language Understanding

Natural Language Understanding is an important field of Natural Language Processing which contains various tasks such as text classification, natural language inference and story comprehension. Applications enabled by natural language understanding range from question answering to automated reasoning.

Source: Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1191–1200 of 1978 papers

Title	Date	Tasks	Status
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning	Aug 12, 2019	intent-classificationIntent Classification	—Unverified
Active Learning for New Domains in Natural Language Understanding	Oct 3, 2018	Active LearningGeneral Classification	—Unverified
AdaPRL: Adaptive Pairwise Regression Learning with Uncertainty Estimation for Universal Regression Tasks	Jan 10, 2025	Age EstimationMulti-Task Learning	—Unverified
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs	Oct 18, 2023	Decision MakingNatural Language Understanding	—Unverified
Adapting Task-Oriented Dialogue Models for Email Conversations	Aug 19, 2022	Intent DetectionNatural Language Understanding	—Unverified
A Dataset of General-Purpose Rebuttal	Sep 1, 2019	Natural Language UnderstandingResponse Generation	—Unverified
Addition is All You Need for Energy-efficient Language Models	Oct 1, 2024	AllNatural Language Understanding	—Unverified
A deep learning approach for understanding natural language commands for mobile service robots	Jul 9, 2018	Action DetectionIntent Detection	—Unverified
A Deep Learning System for Domain-specific Speech Recognition	Mar 18, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
ADEPT: An Adjective-Dependent Plausibility Task	Aug 1, 2021	Common Sense ReasoningNatural Language Understanding	—Unverified

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All datasets PDP60 STREUSLE LexGLUE DialoGLUE fewshot DialoGLUE full GLUE

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	HNN	Accuracy	90	—	Unverified
2	BERT-large 340M	Accuracy	78.3	—	Unverified
3	UDSSM-II (ensemble)	Accuracy	78.3	—	Unverified
4	UDSSM-I (ensemble)	Accuracy	76.7	—	Unverified
5	DSSM	Accuracy	75	—	Unverified
6	UDSSM-II	Accuracy	75	—	Unverified
7	BERT-base 110M + MAS	Accuracy	68.3	—	Unverified
8	USSM + Supervised Deepnet + 3 Knowledge Bases	Accuracy	66.7	—	Unverified
9	Word-level CNN+LSTM (full scoring)	Accuracy	60	—	Unverified
10	Subword-level Transformer LM	Accuracy	58.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT (pred POS/lemmas)	Tags (Full) Acc	82.5	—	Unverified
2	BERT (none)	Tags (Full) Acc	82	—	Unverified
3	BERT (gold POS/lemmas)	Tags (Full) Acc	81	—	Unverified
4	GloVe (gold POS/lemmas)	Tags (Full) Acc	79.3	—	Unverified
5	RoBERTa + Linear	Full F1 (Preps)	78.2	—	Unverified
6	GloVe (none)	Tags (Full) Acc	77.5	—	Unverified
7	GloVe (pred POS/lemmas)	Tags (Full) Acc	77.1	—	Unverified
8	SVM (feature-rich, gold syntax)	Role F1 (Preps)	62.2	—	Unverified
9	BiLSTM + MLP (gold syntax)	Role F1 (Preps)	62.2	—	Unverified
10	SVM (feature-rich, auto syntax)	Role F1 (Preps)	58.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CaseLaw-BERT	CaseHOLD	75.6	—	Unverified
2	Legal-BERT	CaseHOLD	75.1	—	Unverified
3	DeBERTa	CaseHOLD	72.1	—	Unverified
4	Longformer	CaseHOLD	72	—	Unverified
5	RoBERTa	CaseHOLD	71.7	—	Unverified
6	BERT	CaseHOLD	70.7	—	Unverified
7	BigBird	CaseHOLD	70.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ConvBERT-DG	Average	74.6	—	Unverified
2	ConvBERT-DG + Pre + Multi	Average	73.8	—	Unverified
3	mslm	Average	73.49	—	Unverified
4	ConvBERT + Pre + Multi	Average	68.22	—	Unverified
5	BanLanGen	Average	39.16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ConvBERT + Pre + Multi	Average	86.89	—	Unverified
2	mslm	Average	85.83	—	Unverified
3	ConvBERT-DG + Pre + Multi	Average	85.34	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MT-DNN-SMART	Average	89.9	—	Unverified
2	BERT-LARGE	Average	82.1	—	Unverified