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 151–200 of 1978 papers

TitleStatusHype
Joint Prompt Optimization of Stacked LLMs using Variational InferenceCode1
Dual Supervised Learning for Natural Language Understanding and GenerationCode1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
Debiasing Methods in Natural Language Understanding Make Bias More AccessibleCode1
CSKG: The CommonSense Knowledge GraphCode1
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal NuancesCode1
CREAK: A Dataset for Commonsense Reasoning over Entity KnowledgeCode1
C-STS: Conditional Semantic Textual SimilarityCode1
DVMNet++: Rethinking Relative Pose Estimation for Unseen ObjectsCode1
From Black Boxes to Conversations: Incorporating XAI in a Conversational AgentCode1
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language ModelsCode1
Cross-Lingual Semantic Role Labeling with High-Quality Translated Training CorpusCode1
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningCode1
CTRAN: CNN-Transformer-based Network for Natural Language UnderstandingCode1
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about NegationCode1
Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language ModelsCode1
ConFiguRe: Exploring Discourse-level Chinese Figures of SpeechCode1
DeLoRA: Decoupling Angles and Strength in Low-rank AdaptationCode1
A Sequence-to-Sequence Approach to Dialogue State TrackingCode1
A Large-scale Comprehensive Abusiveness Detection Dataset with Multifaceted Labels from RedditCode1
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and GenerationCode1
Distilling Large Vision-Language Model with Out-of-Distribution GeneralizabilityCode1
ALBETO and DistilBETO: Lightweight Spanish Language ModelsCode1
DroidCall: A Dataset for LLM-powered Android Intent InvocationCode1
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge GraphsCode1
Active Learning by Acquiring Contrastive ExamplesCode1
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and BetterCode1
Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical SemanticsCode1
Conic10K: A Challenging Math Problem Understanding and Reasoning DatasetCode1
Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and LanguageCode1
Empathetic BERT2BERT Conversational Model: Learning Arabic Language Generation with Little DataCode1
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT PerspectiveCode1
End-to-End Slot Alignment and Recognition for Cross-Lingual NLUCode1
Enhancing Language Representation with Constructional Information for Natural Language UnderstandingCode1
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from TextCode1
EPIE Dataset: A Corpus For Possible Idiomatic ExpressionsCode1
AllenNLP: A Deep Semantic Natural Language Processing PlatformCode1
Evaluating Scoped Meaning RepresentationsCode1
CLUES: Few-Shot Learning Evaluation in Natural Language UnderstandingCode1
A Surprisingly Robust Trick for Winograd Schema ChallengeCode1
Does It Make Sense? And Why? A Pilot Study for Sense Making and ExplanationCode1
A Win-win Deal: Towards Sparse and Robust Pre-trained Language ModelsCode1
Extracting Event Temporal Relations via Hyperbolic GeometryCode1
Fact-level Extractive Summarization with Hierarchical Graph Mask on BERTCode1
A Dataset for Statutory Reasoning in Tax Law Entailment and Question AnsweringCode1
A Survey of RWKVCode1
FewCLUE: A Chinese Few-shot Learning Evaluation BenchmarkCode1
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language UnderstandingCode1
AceGPT, Localizing Large Language Models in ArabicCode1
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESuppositionCode1
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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