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 751–800 of 1978 papers

TitleStatusHype
Leveraging Affirmative Interpretations from Negation Improves Natural Language UnderstandingCode0
Analyzing Multi-Task Learning for Abstractive Text SummarizationCode1
Inducer-tuning: Connecting Prefix-tuning and Adapter-tuningCode1
IDK-MRC: Unanswerable Questions for Indonesian Machine Reading ComprehensionCode0
ExPUNations: Augmenting Puns with Keywords and ExplanationsCode0
Training Dynamics for Curriculum Learning: A Study on Monolingual and Cross-lingual NLU—0
Prompt-Tuning Can Be Much Better Than Fine-Tuning on Cross-lingual Understanding With Multilingual Language ModelsCode1
InforMask: Unsupervised Informative Masking for Language Model PretrainingCode1
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer EnsembleCode0
Language Detoxification with Attribute-Discriminative Latent SpaceCode0
Explainable Slot Type Attentions to Improve Joint Intent Detection and Slot Filling—0
Team Flow at DRC2022: Pipeline System for Travel Destination Recommendation Task in Spoken Dialogue—0
Textual Entailment Recognition with Semantic Features from Empirical Text Representation—0
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice PerspectiveCode4
Knowledge Prompting in Pre-trained Language Model for Natural Language UnderstandingCode1
Revisiting the Roles of "Text" in Text Games—0
Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue—0
Can Language Representation Models Think in Bets?—0
DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank AdaptationCode4
A Win-win Deal: Towards Sparse and Robust Pre-trained Language ModelsCode1
Instance Regularization for Discriminative Language Model Pre-trainingCode0
Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training—0
Parameter-Efficient Tuning with Special Token AdaptationCode0
Event Extraction: A Survey—0
Time Will Change Things: An Empirical Study on Dynamic Language Understanding in Social Media Classification—0
Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer—0
Explaining Patterns in Data with Language Models via Interpretable AutopromptingCode1
Understanding Prior Bias and Choice Paralysis in Transformer-based Language Representation Models through Four Experimental Probes—0
Evaluating Coreference Resolvers on Community-based Question Answering: From Rule-based to State of the ArtCode0
TextGraphs-16 Natural Language Premise Selection Task: Zero-Shot Premise Selection with Prompting Generative Language Models—0
Building Korean Linguistic Resource for NLU Data Generation of Banking App CS Dialog System—0
ParaZh-22M: A Large-Scale Chinese Parabank via Machine Translation—0
A Transformer-based Threshold-Free Framework for Multi-Intent NLU—0
Competence-based Question Generation—0
RSGT: Relational Structure Guided Temporal Relation Extraction—0
Aligning Multilingual Embeddings for Improved Code-switched Natural Language UnderstandingCode0
Machine Reading, Fast and Slow: When Do Models “Understand” Language?—0
To What Extent Do Natural Language Understanding Datasets Correlate to Logical Reasoning? A Method for Diagnosing Logical Reasoning.—0
Are Visual-Linguistic Models Commonsense Knowledge Bases?Code0
Improving Commonsense Contingent Reasoning by Pseudo-data and Its Application to the Related Tasks—0
Does Meta-learning Help mBERT for Few-shot Question Generation in a Cross-lingual Transfer Setting for Indic Languages?—0
EventBERT: Incorporating Event-based Semantics for Natural Language Understanding—0
Improving Event Temporal Relation Classification via Auxiliary Label-Aware Contrastive Learning—0
Dialog Acts for Task-Driven Embodied Agents—0
Representing Affect Information in Word Embeddings—0
ConFiguRe: Exploring Discourse-level Chinese Figures of SpeechCode1
Adaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement LearningCode0
Belief Revision based Caption Re-ranker with Visual Semantic InformationCode1
Can Offline Reinforcement Learning Help Natural Language Understanding?—0
Machine Reading, Fast and Slow: When Do Models "Understand" Language?—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