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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 1101–1150 of 1978 papers

TitleStatusHype
RSGT: Relational Structure Guided Temporal Relation Extraction—0
SAE-SSV: Supervised Steering in Sparse Representation Spaces for Reliable Control of Language Models—0
Safeguarding Decentralized Social Media: LLM Agents for Automating Community Rule Compliance—0
SAPPHIRE: Simple Aligner for Phrasal Paraphrase with Hierarchical Representation—0
Sattiy at SemEval-2021 Task 9: An Ensemble Solution for Statement Verification and Evidence Finding with Tables—0
SAUCE: Truncated Sparse Document Signature Bit-Vectors for Fast Web-Scale Corpus Expansion—0
ScaLA: Accelerating Adaptation of Pre-Trained Transformer-Based Language Models via Efficient Large-Batch Adversarial Noise—0
Scalable Prompt Generation for Semi-supervised Learning with Language Models—0
Nl2Hltl2Plan: Scaling Up Natural Language Understanding for Multi-Robots Through Hierarchical Temporal Logic Task Representation—0
Schema Aware Semantic Reasoning for Interpreting Natural Language Queries in Enterprise Settings—0
Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentation—0
SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline—0
SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese—0
Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension—0
Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing—0
Selecting Machine-Translated Data for Quick Bootstrapping of a Natural Language Understanding System—0
Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages—0
Self Generated Wargame AI: Double Layer Agent Task Planning Based on Large Language Model—0
Self-Knowledge Distillation for Learning Ambiguity—0
Self-supervised Learning for Large-scale Item Recommendations—0
Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU—0
Self-training with Few-shot Rationalization—0
Semantic Change Characterization with LLMs using Rhetorics—0
Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding—0
Semantic Diversity for Natural Language Understanding Evaluation in Dialog Systems—0
Semantic Grounding in Dialogue for Complex Problem Solving—0
Semantic Loss Application to Entity Relation Recognition—0
Semantic maps and metrics for science Semantic maps and metrics for science using deep transformer encoders—0
Semantics-Aware Inferential Network for Natural Language Understanding—0
Semantic similarity estimation for domain specific data using BERT and other techniques—0
Semantic Slot Prediction on low corpus data using finite user defined list—0
Semantic Wave Functions: Exploring Meaning in Large Language Models Through Quantum Formalism—0
Semi-Supervised Few-Shot Intent Classification and Slot Filling—0
Semi-supervised Intent Discovery with Contrastive Learning—0
Semi-supervised Interactive Intent Labeling—0
Semi-Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models—0
Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer—0
SenseBERT: Driving Some Sense into BERT—0
SenticNet 7: A Commonsense-based Neurosymbolic AI Framework for Explainable Sentiment Analysis—0
Sequential Cross-Document Coreference Resolution—0
Shortcut Learning of Large Language Models in Natural Language Understanding—0
ShortcutLens: A Visual Analytics Approach for Exploring Shortcuts in Natural Language Understanding Dataset—0
Show Us the Way: Learning to Manage Dialog from Demonstrations—0
Simple and Effective Gradient-Based Tuning of Sequence-to-Sequence Models—0
Simple Contrastive Representation Adversarial Learning for NLP Tasks—0
Situated Incremental Natural Language Understanding using a Multimodal, Linguistically-driven Update Model—0
Sketching a Linguistically-Driven Reasoning Dialog Model for Social Talk—0
SkillBot: Towards Automatic Skill Development via User Demonstration—0
SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills—0
Skeleton: A New Framework for Accelerating Language Models via Task Neuron Localized Prompt Tuning—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