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 1476–1500 of 1978 papers

Title	Date	Tasks	Status
Direct Network Transfer: Transfer Learning of Sentence Embeddings for Semantic Similarity	Apr 20, 2018	Natural Language UnderstandingSemantic Similarity	—Unverified
Discrete Reasoning Templates for Natural Language Understanding	Apr 5, 2021	Natural Language UnderstandingReading Comprehension	—Unverified
Discrete Word Embedding for Logical Natural Language Understanding	Aug 26, 2020	Decision MakingNatural Language Understanding	—Unverified
Distill and Replay for Continual Language Learning	Dec 1, 2020	Language ModellingNatural Language Understanding	—Unverified
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization	Aug 8, 2024	Graph ClassificationGraph Learning	—Unverified
DKPLM: Decomposable Knowledge-enhanced Pre-trained Language Model for Natural Language Understanding	Dec 2, 2021	Knowledge GraphsKnowledge Probing	—Unverified
DLGNet-Task: An End-to-end Neural Network Framework for Modeling Multi-turn Multi-domain Task-Oriented Dialogue	Oct 4, 2020	Dialogue GenerationNatural Language Understanding	—Unverified
Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding	Feb 12, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Dobby: A Conversational Service Robot Driven by GPT-4	Oct 10, 2023	AI AgentDecision Making	—Unverified
Document-Level Neural Machine Translation Using BERT as Context Encoder	Dec 1, 2020	DecoderDocument Level Machine Translation	—Unverified
Does Knowledge Help General NLU? An Empirical Study	Sep 1, 2021	Common Sense ReasoningLanguage Modeling	—Unverified
Does Meta-learning Help mBERT for Few-shot Question Generation in a Cross-lingual Transfer Setting for Indic Languages?	Oct 1, 2022	Cross-Lingual TransferLanguage Modeling	—Unverified
Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers	Apr 4, 2024	FairnessInformation Retrieval	—Unverified
Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding	Apr 1, 2016	Domain AdaptationMulti-Task Learning	—Unverified
Do Multi-Sense Embeddings Improve Natural Language Understanding?	Jun 2, 2015	named-entity-recognitionNamed Entity Recognition	—Unverified
Looking Right is Sometimes Right: Investigating the Capabilities of Decoder-only LLMs for Sequence Labeling	Jan 25, 2024	Causal Language ModelingDecoder	—Unverified
Do Not Worry if You Do Not Have Data: Building Pretrained Language Models Using Translationese	Mar 20, 2024	Machine TranslationNatural Language Understanding	—Unverified
Don't Parse, Insert: Multilingual Semantic Parsing with Insertion Based Decoding	Oct 8, 2020	Cross-Lingual TransferNatural Language Understanding	—Unverified
Don't Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMs	May 24, 2023	Natural Language Understanding	—Unverified
DoRO: Disambiguation of referred object for embodied agents	Jul 28, 2022	Natural Language UnderstandingObject	—Unverified
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain	Jun 11, 2019	Multi-Task LearningNatural Language Understanding	—Unverified
On the Importance of Word Order Information in Cross-lingual Sequence Labeling	Jan 30, 2020	named-entity-recognitionNamed Entity Recognition	—Unverified
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation	May 10, 2024	Federated LearningNatural Language Understanding	—Unverified
BPDec: Unveiling the Potential of Masked Language Modeling Decoder in BERT pretraining	Jan 29, 2024	DecoderLanguage Modeling	—Unverified
Dropping Networks for Transfer Learning	Apr 23, 2018	Few-Shot LearningNatural Language Inference	—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	UDSSM-II (ensemble)	Accuracy	78.3	—	Unverified
3	BERT-large 340M	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