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

Showing 501550 of 1978 papers

TitleStatusHype
Language-Agnostic Syllabification with Neural Sequence LabelingCode0
ConsistentEE: A Consistent and Hardness-Guided Early Exiting Method for Accelerating Language Models InferenceCode0
Language Detoxification with Attribute-Discriminative Latent SpaceCode0
Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with SubwordsCode0
BasqueGLUE: A Natural Language Understanding Benchmark for BasqueCode0
Design Challenges for a Multi-Perspective Search EngineCode0
CoNFET: An English Sentence to Emojis Translation AlgorithmCode0
Concept Tagging for Natural Language Understanding: Two Decadelong Algorithm DevelopmentCode0
KEHRL: Learning Knowledge-Enhanced Language Representations with Hierarchical Reinforcement LearningCode0
Comprehensive Supersense Disambiguation of English Prepositions and PossessivesCode0
AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource LanguagesCode0
Joint Semantic Analysis with Document-Level Cross-Task Coherence RewardsCode0
Complement Objective TrainingCode0
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding ModelsCode0
Joint Slot Filling and Intent Detection via Capsule Neural NetworksCode0
Jack the Reader -- A Machine Reading FrameworkCode0
Ambiguity Meets Uncertainty: Investigating Uncertainty Estimation for Word Sense DisambiguationCode0
Commonsense Knowledge Mining from Term DefinitionsCode0
Is this sentence valid? An Arabic Dataset for Commonsense ValidationCode0
Adaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement LearningCode0
Is Supervised Syntactic Parsing Beneficial for Language Understanding? An Empirical InvestigationCode0
Collapsed Language Models Promote FairnessCode0
Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language UnderstandingCode0
Is the Understanding of Explicit Discourse Relations Required in Machine Reading Comprehension?Code0
Intent Features for Rich Natural Language UnderstandingCode0
Intent Detection and Entity Extraction from BioMedical LiteratureCode0
Intra-Correlation Encoding for Chinese Sentence Intention MatchingCode0
A Study on the Calibration of In-context LearningCode0
Instance Regularization for Discriminative Language Model Pre-trainingCode0
MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of GradientsCode0
INSET: Sentence Infilling with INter-SEntential TransformerCode0
Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine TuningCode0
Investigating the (De)Composition Capabilities of Large Language Models in Natural-to-Formal Language ConversionCode0
CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU TasksCode0
Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding TasksCode0
CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition AlignmentCode0
ACCEPT: Adaptive Codebook for Composite and Efficient Prompt TuningCode0
Aligning Multilingual Embeddings for Improved Code-switched Natural Language UnderstandingCode0
Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement LearningCode0
Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive SurveyCode0
Improving Tokenisation by Alternative Treatment of SpacesCode0
Improving Non-autoregressive Generation with Mixup TrainingCode0
AlexU-AL at SemEval-2022 Task 6: Detecting Sarcasm in Arabic Text Using Deep Learning TechniquesCode0
Improving the Efficiency of Visually Augmented Language ModelsCode0
Improving In-Context Learning with Small Language Model EnsemblesCode0
Improving Grounded Natural Language Understanding through Human-Robot DialogCode0
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation FusionCode0
Accelerating Natural Language Understanding in Task-Oriented DialogCode0
Classification of telicity using cross-linguistic annotation projectionCode0
Improving Bias Mitigation through Bias Experts in Natural Language UnderstandingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HNNAccuracy90Unverified
2UDSSM-II (ensemble)Accuracy78.3Unverified
3BERT-large 340MAccuracy78.3Unverified
4UDSSM-I (ensemble)Accuracy76.7Unverified
5DSSMAccuracy75Unverified
6UDSSM-IIAccuracy75Unverified
7BERT-base 110M + MASAccuracy68.3Unverified
8USSM + Supervised Deepnet + 3 Knowledge BasesAccuracy66.7Unverified
9Word-level CNN+LSTM (full scoring)Accuracy60Unverified
10Subword-level Transformer LMAccuracy58.3Unverified
#ModelMetricClaimedVerifiedStatus
1BERT (pred POS/lemmas)Tags (Full) Acc82.5Unverified
2BERT (none)Tags (Full) Acc82Unverified
3BERT (gold POS/lemmas)Tags (Full) Acc81Unverified
4GloVe (gold POS/lemmas)Tags (Full) Acc79.3Unverified
5RoBERTa + LinearFull F1 (Preps)78.2Unverified
6GloVe (none)Tags (Full) Acc77.5Unverified
7GloVe (pred POS/lemmas)Tags (Full) Acc77.1Unverified
8SVM (feature-rich, gold syntax)Role F1 (Preps)62.2Unverified
9BiLSTM + MLP (gold syntax)Role F1 (Preps)62.2Unverified
10SVM (feature-rich, auto syntax)Role F1 (Preps)58.2Unverified
#ModelMetricClaimedVerifiedStatus
1CaseLaw-BERTCaseHOLD75.6Unverified
2Legal-BERTCaseHOLD75.1Unverified
3DeBERTaCaseHOLD72.1Unverified
4LongformerCaseHOLD72Unverified
5RoBERTaCaseHOLD71.7Unverified
6BERTCaseHOLD70.7Unverified
7BigBirdCaseHOLD70.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConvBERT-DGAverage74.6Unverified
2ConvBERT-DG + Pre + MultiAverage73.8Unverified
3mslmAverage73.49Unverified
4ConvBERT + Pre + MultiAverage68.22Unverified
5BanLanGenAverage39.16Unverified
#ModelMetricClaimedVerifiedStatus
1ConvBERT + Pre + MultiAverage86.89Unverified
2mslmAverage85.83Unverified
3ConvBERT-DG + Pre + MultiAverage85.34Unverified
#ModelMetricClaimedVerifiedStatus
1MT-DNN-SMARTAverage89.9Unverified
2BERT-LARGEAverage82.1Unverified