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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 1301–1350 of 1978 papers

TitleStatusHype
Unlocking Smarter Device Control: Foresighted Planning with a World Model-Driven Code Execution Approach—0
Unmasking Digital Falsehoods: A Comparative Analysis of LLM-Based Misinformation Detection Strategies—0
Unreasonable Effectiveness of Rule-Based Heuristics in Solving Russian SuperGLUE Tasks—0
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning—0
Unsupervised Neologism Normalization Using Embedding Space Mapping—0
Unsupervised Pre-training for Natural Language Generation: A Literature Review—0
User Adaptive Language Learning Chatbots with a Curriculum—0
User Intent Inference for Web Search and Conversational Agents—0
Using Alternate Representations of Text for Natural Language Understanding—0
Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge—0
Using BERT Encoding and Sentence-Level Language Model for Sentence Ordering—0
Using multiple ASR hypotheses to boost i18n NLU performance—0
Using NLU in Context for Question Answering: Improving on Facebook's bAbI Tasks—0
Using Pause Information for More Accurate Entity Recognition—0
Variance Pruning: Pruning Language Models via Temporal Neuron Variance—0
Rethinking the Instruction Quality: LIFT is What You Need—0
VASTA: A Vision and Language-assisted Smartphone Task Automation System—0
VectorFit : Adaptive Singular & Bias Vector Fine-Tuning of Pre-trained Foundation Models—0
Verb Metaphor Detection via Contextual Relation Learning—0
ViANLI: Adversarial Natural Language Inference for Vietnamese—0
Vision-Language-Action Models: Concepts, Progress, Applications and Challenges—0
Visual Attention Model for Name Tagging in Multimodal Social Media—0
Visually Grounded Language Learning: a review of language games, datasets, tasks, and models—0
Visual question answering: from early developments to recent advances -- a survey—0
VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension—0
VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding—0
WaLDORf: Wasteless Language-model Distillation On Reading-comprehension—0
WALNUT: A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding—0
Warped Language Models for Noise Robust Language Understanding—0
Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs—0
Web-API-Based Chatbot Generation with Analysis and Expansion for Training Sentences—0
We Need to Talk About Classification Evaluation Metrics in NLP—0
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding—0
What Makes Good In-Context Examples for GPT-3?—0
What Makes Machine Reading Comprehension Questions Difficult? Investigating Variation in Passage Sources and Question Types—0
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
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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