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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 951–1000 of 1978 papers

TitleStatusHype
Neighbor Contextual Information Learners for Joint Intent and Slot Prediction—0
NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models—0
Neural Architecture Search for Natural Language Understanding—0
Neural Machine Translation For Paraphrase Generation—0
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration—0
Neural Networks for Text Correction and Completion in Keyboard Decoding—0
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version)—0
Neural Text Normalization with Subword Units—0
NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment—0
Neurosymbolic Graph Enrichment for Grounded World Models—0
Newsalyze: Effective Communication of Person-Targeting Biases in News Articles—0
NewsEmbed: Modeling News through Pre-trained Document Representations—0
Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL—0
NLU-Co at SemEval-2020 Task 5: NLU/SVM Based Model Apply Tocharacterise and Extract Counterfactual Items on Raw Data—0
NLU for Game-based Learning in Real: Initial Evaluations—0
Noise Robust Named Entity Understanding for Voice Assistants—0
Nora: The Well-Being Coach—0
Not All Attention Is All You Need—0
NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks—0
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM—0
OmniGeo: Towards a Multimodal Large Language Models for Geospatial Artificial Intelligence—0
On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation—0
On Degrees of Freedom in Defining and Testing Natural Language Understanding—0
SkillNet-NLU: A Sparsely Activated Model for General-Purpose Natural Language Understanding—0
One-vs-All Models for Asynchronous Training: An Empirical Analysis—0
Only One Relation Possible? Modeling the Ambiguity in Event Temporal Relation Extraction—0
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency—0
On the cross-lingual transferability of multilingual prototypical models across NLU tasks—0
On the Importance of Attention in Meta-Learning for Few-Shot Text Classification—0
On the Limits of Learning to Actively Learn Semantic Representations—0
On the N-gram Approximation of Pre-trained Language Models—0
On the Role of Corpus Ordering in Language Modeling—0
On the Winograd Schema: Situating Language Understanding in the Data-Information-Knowledge Continuum—0
Ontology-based question answering over corporate structured data—0
Ontology Population using LLMs—0
OntoType: Ontology-Guided and Pre-Trained Language Model Assisted Fine-Grained Entity Typing—0
Optimizing NLU Reranking Using Entity Resolution Signals in Multi-domain Dialog Systems—0
ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension—0
Out of Order: How Important Is The Sequential Order of Words in a Sentence in Natural Language Understanding Tasks?—0
Overcoming Poor Word Embeddings with Word Definitions—0
PAFFA: Premeditated Actions For Fast Agents—0
Painter: Teaching Auto-regressive Language Models to Draw Sketches—0
Pair-Level Supervised Contrastive Learning for Natural Language Inference—0
PALM: Pre-training an Autoencoding\&Autoregressive Language Model for Context-conditioned Generation—0
PanGu-Σ: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing—0
PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System—0
ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations—0
Paraphrase Generation for Semi-Supervised Learning in NLU—0
Paraphrasing in Affirmative Terms Improves Negation Understanding—0
ParaZh-22M: A Large-Scale Chinese Parabank via Machine Translation—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