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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

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Showing 1151–1200 of 1978 papers

TitleStatusHype
What Makes Reading Comprehension Questions Difficult? Investigating Variation in Passage Sources and Question Types—0
"What's my model inside of?": Exploring the role of environments for grounded natural language understanding—0
Adapting Long Context NLM for ASR Rescoring in Conversational Agents—0
What Will it Take to Fix Benchmarking in Natural Language Understanding?—0
When Choosing Plausible Alternatives, Clever Hans can be Clever—0
When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems—0
When Text Embedding Meets Large Language Model: A Comprehensive Survey—0
Where did you tweet from? Inferring the origin locations of tweets based on contextual information—0
Why Robust Natural Language Understanding is a Challenge—0
Will it Blend? Blending Weak and Strong Labeled Data in a Neural Network for Argumentation Mining—0
Word Sense Disambiguation as a Game of Neurosymbolic Darts—0
Would you Rather? A New Benchmark for Learning Machine Alignment with Cultural Values and Social Preferences—0
XDBERT: Distilling Visual Information to BERT from Cross-Modal Systems to Improve Language Understanding—0
XGLUE: A New Benchmark Datasetfor Cross-lingual Pre-training, Understanding and Generation—0
XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Source—0
X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection—0
Yes, No or IDK: The Challenge of Unanswerable Yes/No Questions—0
YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos—0
Zero-Resource Multi-Dialectal Arabic Natural Language Understanding—0
Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables—0
Zero-Shot Learning for Joint Intent and Slot Labeling—0
Zero-Shot Slot and Intent Detection in Low-Resource Languages—0
Zero-shot Slot Filling in the Age of LLMs for Dialogue Systems—0
Challenges and Prospects in Vision and Language Research—0
Zooming Network—0
Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach—0
ChemGraph: An Agentic Framework for Computational Chemistry Workflows—0
3D-RPE: Enhancing Long-Context Modeling Through 3D Rotary Position Encoding—0
AAVENUE: Detecting LLM Biases on NLU Tasks in AAVE via a Novel Benchmark—0
A Brief Survey and Comparative Study of Recent Development of Pronoun Coreference Resolution in English—0
Accurate Word Representations with Universal Visual Guidance—0
A character representation enhanced on-device Intent Classification—0
A Cohesive Distillation Architecture for Neural Language Models—0
A Comparative Analysis of Ethical and Safety Gaps in LLMs using Relative Danger Coefficient—0
A Comparative Analysis of Pretrained Language Models for Text-to-Speech—0
A Comparative Study on Collecting High-Quality Implicit Reasonings at a Large-scale—0
A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering—0
A Complex KBQA System using Multiple Reasoning Paths—0
A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models—0
Action State Update Approach to Dialogue Management—0
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning—0
Active Learning for New Domains in Natural Language Understanding—0
AdaPRL: Adaptive Pairwise Regression Learning with Uncertainty Estimation for Universal Regression Tasks—0
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs—0
Adapting Task-Oriented Dialogue Models for Email Conversations—0
A Dataset of General-Purpose Rebuttal—0
Addition is All You Need for Energy-efficient Language Models—0
A deep learning approach for understanding natural language commands for mobile service robots—0
A Deep Learning System for Domain-specific Speech Recognition—0
ADEPT: An Adjective-Dependent Plausibility Task—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