SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1401–1450 of 1978 papers

TitleStatusHype
Contextual Biasing of Language Models for Speech Recognition in Goal-Oriented Conversational Agents—0
Reweighting Augmented Samples by Minimizing the Maximal Expected LossCode0
Robustly Optimized and Distilled Training for Natural Language Understanding—0
LightMBERT: A Simple Yet Effective Method for Multilingual BERT Distillation—0
Meta-Learning with MAML on Trees—0
Overcoming Poor Word Embeddings with Word Definitions—0
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration—0
Natural Language Understanding for Argumentative Dialogue Systems in the Opinion Building Domain—0
A Linguistic Study on Relevance Modeling in Information Retrieval—0
N-Shot Learning for Augmenting Task-Oriented Dialogue State Tracking—0
Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding—0
From Universal Language Model to Downstream Task: Improving RoBERTa-Based Vietnamese Hate Speech Detection—0
Joint Intent Detection And Slot Filling Based on Continual Learning Model—0
UniT: Multimodal Multitask Learning with a Unified TransformerCode0
MixUp Training Leads to Reduced Overfitting and Improved Calibration for the Transformer Architecture—0
A Relational Tsetlin Machine with Applications to Natural Language Understanding—0
Have Attention Heads in BERT Learned Constituency Grammar?—0
Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding—0
A Metamodel and Framework for Artificial General Intelligence From Theory to Practice—0
Speech-language Pre-training for End-to-end Spoken Language Understanding—0
Statistically Profiling Biases in Natural Language Reasoning Datasets and Models—0
A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining—0
The Singleton Fallacy: Why Current Critiques of Language Models Miss the Point—0
Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with SubwordsCode0
Commonsense Knowledge Mining from Term DefinitionsCode0
An Unsupervised Language-Independent Entity Disambiguation Method and its Evaluation on the English and Persian Languages—0
Fine-tuning BERT-based models for Plant Health Bulletin ClassificationCode0
Knowledge-driven Natural Language Understanding of English Text and its Applications—0
Exploring Transitivity in Neural NLI Models through VeridicalityCode0
Training Multilingual Pre-trained Language Model with Byte-level Subwords—0
Multi-sense embeddings through a word sense disambiguation processCode0
A survey of joint intent detection and slot-filling models in natural language understanding—0
Exploring Lexical Irregularities in Hypothesis-Only Models of Natural Language Inference—0
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding ModelsCode0
Understanding in Artificial Intelligence—0
A character representation enhanced on-device Intent Classification—0
EfficientQA : a RoBERTa Based Phrase-Indexed Question-Answering System—0
CoNFET: An English Sentence to Emojis Translation AlgorithmCode0
RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge—0
HyperGrid Transformers: Towards A Single Model for Multiple Tasks—0
Monte-Carlo Planning and Learning with Language Action Value Estimates—0
Learning Chess Blindfolded—0
Discourse-level Relation Extraction via Graph Pooling—0
Pre-training Text-to-Text Transformers to Write and Reason with Concepts—0
Later Span Adaptation for Language Understanding—0
Coreference Reasoning in Machine Reading ComprehensionCode0
Out of Order: How Important Is The Sequential Order of Words in a Sentence in Natural Language Understanding Tasks?—0
Accurate Word Representations with Universal Visual Guidance—0
My Teacher Thinks The World Is Flat! Interpreting Automatic Essay Scoring MechanismCode0
I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling—0
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All datasetsPDP60STREUSLELexGLUEDialoGLUE fewshotDialoGLUE fullGLUE

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HNNAccuracy90—Unverified
2UDSSM-II (ensemble)Accuracy78.3—Unverified
3BERT-large 340MAccuracy78.3—Unverified
4UDSSM-I (ensemble)Accuracy76.7—Unverified
5DSSMAccuracy75—Unverified
6UDSSM-IIAccuracy75—Unverified
7BERT-base 110M + MASAccuracy68.3—Unverified
8USSM + Supervised Deepnet + 3 Knowledge BasesAccuracy66.7—Unverified
9Word-level CNN+LSTM (full scoring)Accuracy60—Unverified
10Subword-level Transformer LMAccuracy58.3—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT (pred POS/lemmas)Tags (Full) Acc82.5—Unverified
2BERT (none)Tags (Full) Acc82—Unverified
3BERT (gold POS/lemmas)Tags (Full) Acc81—Unverified
4GloVe (gold POS/lemmas)Tags (Full) Acc79.3—Unverified
5RoBERTa + LinearFull F1 (Preps)78.2—Unverified
6GloVe (none)Tags (Full) Acc77.5—Unverified
7GloVe (pred POS/lemmas)Tags (Full) Acc77.1—Unverified
8SVM (feature-rich, gold syntax)Role F1 (Preps)62.2—Unverified
9BiLSTM + MLP (gold syntax)Role F1 (Preps)62.2—Unverified
10SVM (feature-rich, auto syntax)Role F1 (Preps)58.2—Unverified
#ModelMetricClaimedVerifiedStatus
1CaseLaw-BERTCaseHOLD75.6—Unverified
2Legal-BERTCaseHOLD75.1—Unverified
3DeBERTaCaseHOLD72.1—Unverified
4LongformerCaseHOLD72—Unverified
5RoBERTaCaseHOLD71.7—Unverified
6BERTCaseHOLD70.7—Unverified
7BigBirdCaseHOLD70.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ConvBERT-DGAverage74.6—Unverified
2ConvBERT-DG + Pre + MultiAverage73.8—Unverified
3mslmAverage73.49—Unverified
4ConvBERT + Pre + MultiAverage68.22—Unverified
5BanLanGenAverage39.16—Unverified
#ModelMetricClaimedVerifiedStatus
1ConvBERT + Pre + MultiAverage86.89—Unverified
2mslmAverage85.83—Unverified
3ConvBERT-DG + Pre + MultiAverage85.34—Unverified
#ModelMetricClaimedVerifiedStatus
1MT-DNN-SMARTAverage89.9—Unverified
2BERT-LARGEAverage82.1—Unverified