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 1901–1950 of 1978 papers

TitleStatusHype
Story Comprehension for Predicting What Happens Next—0
Underspecification in Natural Language Understanding for Dialog Automation—0
Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension—0
Translating Phrases in Neural Machine Translation—0
Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language InferenceCode0
A Joint Model for Semantic Sequences: Frames, Entities, Sentiments—0
Evaluating Natural Language Understanding Services for Conversational Question Answering SystemsCode0
A Tale of Two DRAGGNs: A Hybrid Approach for Interpreting Action-Oriented and Goal-Oriented InstructionsCode0
Implicit Entity Linking in Tweets—0
Predicting Causes of Reformulation in Intelligent Assistants—0
Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability—0
Dynamic Integration of Background Knowledge in Neural NLU Systems—0
Text Summarization using Abstract Meaning RepresentationCode0
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface—0
Integrated Learning of Dialog Strategies and Semantic Parsing—0
Neural Models for Sequence ChunkingCode0
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version)—0
Unit Dependency Graph and its Application to Arithmetic Word Problem Solving—0
End-to-End Joint Learning of Natural Language Understanding and Dialogue ManagerCode0
Dialog-based Language Learning—0
Neural Architecture Search with Reinforcement LearningCode0
Learning Recurrent Span Representations for Extractive Question AnsweringCode0
Tutorial on Answering Questions about Images with Deep LearningCode0
Knowledge as a Teacher: Knowledge-Guided Structural Attention Networks—0
Modality: logic, semantics, annotation and machine learning—0
A Large-Scale Multilingual Disambiguation of Glosses—0
WikiReading: A Novel Large-scale Language Understanding Task over WikipediaCode0
COREALMLIB: An ALM Library Translated from the Component Library—0
Processing Natural Language About Ongoing ActionsCode0
CFGs-2-NLU: Sequence-to-Sequence Learning for Mapping Utterances to Semantics and Pragmatics—0
Constructing a Natural Language Inference Dataset using Generative Neural NetworksCode0
Neural Semantic EncodersCode0
A Probabilistic Generative Grammar for Semantic ParsingCode0
Two Discourse Driven Language Models for Semantics—0
Spectral decomposition method of dialog state tracking via collective matrix factorization—0
Dialog state tracking, a machine reading approach using Memory Network—0
Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks—0
A Lexical Resource of Hebrew Verb-Noun Multi-Word Expressions—0
The Negochat Corpus of Human-agent Negotiation Dialogues—0
Dialog-based Language Learning—0
Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding—0
Probabilistic Reasoning via Deep Learning: Neural Association Models—0
Learning Executable Semantic Parsers for Natural Language Understanding—0
Leveraging Sentence-level Information with Encoder LSTM for Semantic Slot Filling—0
Modeling Variations of First-Order Horn Abduction in Answer Set ProgrammingCode0
Ask, and shall you receive?: Understanding Desire Fulfillment in Natural Language Text—0
Natural Language Understanding with Distributed RepresentationCode0
Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing—0
Class Vectors: Embedding representation of Document Classes—0
A Neural Conversational ModelCode0
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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