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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 1651–1700 of 1978 papers

TitleStatusHype
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding—0
Graph Retrieval-Augmented LLM for Conversational Recommendation Systems—0
Grasping the Finer Point: A Supervised Similarity Network for Metaphor Detection—0
GREEN: Generative Radiology Report Evaluation and Error Notation—0
Language Conditioned Imitation Learning over Unstructured Data—0
GUIDE: Graphical User Interface Data for Execution—0
Gunrock 2.0: A User Adaptive Social Conversational System—0
Hakim: Farsi Text Embedding Model—0
Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models—0
Handling Noun-Noun Coreference in Tamil—0
Have Attention Heads in BERT Learned Constituency Grammar?—0
Hierarchical Encoders for Modeling and Interpreting Screenplays—0
HierTOD: A Task-Oriented Dialogue System Driven by Hierarchical Goals—0
Hi, how can I help you?: Automating enterprise IT support help desks—0
History-Aware Question Answering in a Blocks World Dialogue System—0
How Can Large Language Models Understand Spatial-Temporal Data?—0
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?—0
How Does Data Corruption Affect Natural Language Understanding Models? A Study on GLUE datasets—0
How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks—0
How to Select One Among All ? An Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding—0
Human-like Cognitive Generalization for Large Models via Brain-in-the-loop Supervision—0
Hybrid MemNet for Extractive Summarization—0
Hyperbolic Deep Learning for Chinese Natural Language Understanding—0
HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections—0
HyperGrid Transformers: Towards A Single Model for Multiple Tasks—0
Hypernymy Detection for Low-Resource Languages via Meta Learning—0
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding—0
HyperPrompt: Prompt-based Task-Conditioning of Transformers—0
IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models—0
ICH-Qwen: A Large Language Model Towards Chinese Intangible Cultural Heritage—0
Identification of Entailment and Contradiction Relations between Natural Language Sentences: A Neurosymbolic Approach—0
Identifying and Resolving Annotation Changes for Natural Language Understanding—0
Identifying Bengali Multiword Expressions using Semantic Clustering—0
Identifying Motion Entities in Natural Language and A Case Study for Named Entity Recognition—0
IDPG: An Instance-Dependent Prompt Generation Method—0
IDPG: An Instance-Dependent Prompt Generation Method—0
Explicit Contextual Semantics for Text Comprehension—0
I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling—0
CLIPPO: Image-and-Language Understanding from Pixels Only—0
Image-based Natural Language Understanding Using 2D Convolutional Neural Networks—0
Image Captioning at Will: A Versatile Scheme for Effectively Injecting Sentiments into Image Descriptions—0
Imagination-Augmented Natural Language Understanding—0
Implicit Entity Linking in Tweets—0
Improved and Efficient Conversational Slot Labeling through Question Answering—0
Improved and Efficient Conversational Slot Labeling through Question Answering—0
Improved intent classification based on context information using a windows-based approach—0
Improved OOD Generalization via Adversarial Training and Pre-training—0
Improvements and Extensions on Metaphor Detection—0
Improving BERT with Hybrid Pooling Network and Drop Mask—0
Improving Black-box Speech Recognition using Semantic Parsing—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