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

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Showing 851–900 of 1978 papers

TitleStatusHype
Compressing Pre-trained Transformers via Low-Bit NxM Sparsity for Natural Language Understanding—0
Not Cheating on the Turing Test: Towards Grounded Language Learning in Artificial Intelligence—0
Solving Quantitative Reasoning Problems with Language ModelsCode2
ZoDIAC: Zoneout Dropout Injection Attention CalculationCode0
Endowing Language Models with Multimodal Knowledge Graph RepresentationsCode1
Meta Auxiliary Learning for Low-resource Spoken Language Understanding—0
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight ImportanceCode1
Unified BERT for Few-shot Natural Language Understanding—0
Why Robust Natural Language Understanding is a Challenge—0
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems—0
CHQ-Summ: A Dataset for Consumer Healthcare Question SummarizationCode0
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation—0
Transformer based Urdu Handwritten Text Optical Character Reader—0
TCE at Qur'an QA 2022: Arabic Language Question Answering Over Holy Qur'an Using a Post-Processed Ensemble of BERT-based ModelsCode1
Strategy-level Entrainment of Dialogue System Users in a Creative Visual Reference Resolution Task—0
TCE at Qur’an QA 2022: Arabic Language Question Answering Over Holy Qur’an Using a Post-Processed Ensemble of BERT-based ModelsCode1
A Large Interlinked Knowledge Graph of the Italian Cultural Heritage—0
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
Dialogue Act and Slot Recognition in Italian Complex Dialogues—0
BasqueGLUE: A Natural Language Understanding Benchmark for BasqueCode0
BaSCo: An Annotated Basque-Spanish Code-Switching Corpus for Natural Language Understanding—0
Question Modifiers in Visual Question Answering—0
The Robotic Surgery Procedural FramebankCode0
Negation Detection in Dutch Spoken Human-Computer Conversations—0
Exploring Text Recombination for Automatic Narrative Level Detection—0
Towards Building a Spoken Dialogue System for Argument Exploration—0
JGLUE: Japanese General Language Understanding EvaluationCode2
SenticNet 7: A Commonsense-based Neurosymbolic AI Framework for Explainable Sentiment Analysis—0
Étiquetage ou génération de séquences pour la compréhension automatique du langage en contexte d’interaction? (Sequence tagging or sequence generation for Natural Language Understanding ?)—0
A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference—0
E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and GenerationCode0
NLU for Game-based Learning in Real: Initial Evaluations—0
IGLU 2022: Interactive Grounded Language Understanding in a Collaborative Environment at NeurIPS 2022Code0
Automatic question generation based on sentence structure analysis using machine learning approach—0
InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction TuningCode1
GisPy: A Tool for Measuring Gist Inference Score in TextCode1
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningCode1
When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding SystemsCode0
A Survey on Neural Open Information Extraction: Current Status and Future Directions—0
Vector-Quantized Input-Contextualized Soft Prompts for Natural Language UnderstandingCode1
The Importance of Being Parameters: An Intra-Distillation Method for Serious GainsCode1
Contrastive Representation Learning for Cross-Document Coreference Resolution of Events and Entities—0
Training Efficient CNNS: Tweaking the Nuts and Bolts of Neural Networks for Lighter, Faster and Robust ModelsCode0
Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding—0
Calibration of Natural Language Understanding Models with Venn--ABERS PredictorsCode0
Down and Across: Introducing Crossword-Solving as a New NLP BenchmarkCode0
Enhancing Slot Tagging with Intent Features for Task Oriented Natural Language Understanding using BERT—0
Are Prompt-based Models Clueless?—0
PromptDA: Label-guided Data Augmentation for Prompt-based Few-shot LearnersCode0
A Fast Attention Network for Joint Intent Detection and Slot Filling on Edge Devices—0
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All datasetsPDP60STREUSLELexGLUEDialoGLUE fewshotDialoGLUE fullGLUE

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HNNAccuracy90—Unverified
2BERT-large 340MAccuracy78.3—Unverified
3UDSSM-II (ensemble)Accuracy78.3—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