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 1601–1650 of 1978 papers

TitleStatusHype
Fast and Scalable Expansion of Natural Language Understanding Functionality for Intelligent Agents—0
FedEAT: A Robustness Optimization Framework for Federated LLMs—0
Federated Learning for Emoji Prediction in a Mobile Keyboard—0
Federated Self-Learning with Weak Supervision for Speech Recognition—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding—0
Few-shot Intent Classification and Slot Filling with Retrieved Examples—0
Few-shot Multimodal Multitask Multilingual Learning—0
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF—0
Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?—0
Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers—0
Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers—0
Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning—0
Fine-Tuning BERT for Schema-Guided Zero-Shot Dialogue State Tracking—0
Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks—0
First Train to Generate, then Generate to Train: UnitedSynT5 for Few-Shot NLI—0
FitChat: Conversational Artificial Intelligence Interventions for Encouraging Physical Activity in Older Adults—0
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning—0
FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding—0
Fooling Vision and Language Models Despite Localization and Attention Mechanism—0
Forming Trees with Treeformers—0
FrameNet-like Annotation of Olfactory Information in Texts—0
From Audio to Semantics: Approaches to end-to-end spoken language understanding—0
From Beginner to Expert: Modeling Medical Knowledge into General LLMs—0
From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding—0
From Spatial Relations to Spatial Configurations—0
From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology—0
From Universal Language Model to Downstream Task: Improving RoBERTa-Based Vietnamese Hate Speech Detection—0
From Virtual to Real: A Framework for Verbal Interaction with Robots—0
Fully Unsupervised Crosslingual Semantic Textual Similarity Metric Based on BERT for Identifying Parallel Data—0
Fuse and Adapt: Investigating the Use of Pre-Trained Self-Supervising Learning Models in Limited Data NLU problems—0
Fusion-Eval: Integrating Assistant Evaluators with LLMs—0
Generalized Multiple Intent Conditioned Slot Filling—0
Generating Synthetic Data for Task-Oriented Semantic Parsing with Hierarchical Representations—0
Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings—0
Generative Adversarial Networks for Annotated Data Augmentation in Data Sparse NLU—0
GeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark—0
GeoReasoner: Reasoning On Geospatially Grounded Context For Natural Language Understanding—0
Get Your Model Puzzled: Introducing Crossword-Solving as a New NLP Benchmark—0
GF + MMT = GLF -- From Language to Semantics through LF—0
GLM: General Language Model Pretraining with Autoregressive Blank Infilling—0
Goal-Oriented Chatbot Dialog Management Bootstrapping with Transfer Learning—0
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference—0
GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models—0
GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP—0
GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching—0
GradTS: A Gradient-Based Automatic Auxiliary Task Selection Method Based on Transformer Networks—0
Graph-Based Semi-Supervised Learning for Natural Language Understanding—0
Graph Enhanced Cross-Domain Text-to-SQL Generation—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