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 19011925 of 1978 papers

TitleStatusHype
Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension0
Classification of telicity using cross-linguistic annotation projectionCode0
Translating Phrases in Neural Machine Translation0
Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language InferenceCode0
Evaluating Natural Language Understanding Services for Conversational Question Answering SystemsCode0
A Joint Model for Semantic Sequences: Frames, Entities, Sentiments0
Implicit Entity Linking in Tweets0
A Tale of Two DRAGGNs: A Hybrid Approach for Interpreting Action-Oriented and Goal-Oriented InstructionsCode0
Predicting Causes of Reformulation in Intelligent Assistants0
Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability0
Attention Is All You NeedCode3
Dynamic Integration of Background Knowledge in Neural NLU Systems0
Text Summarization using Abstract Meaning RepresentationCode0
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface0
Integrated Learning of Dialog Strategies and Semantic Parsing0
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 Solving0
End-to-End Joint Learning of Natural Language Understanding and Dialogue ManagerCode0
Dialog-based Language Learning0
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 Networks0
Modality: logic, semantics, annotation and machine learning0
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HNNAccuracy90Unverified
2UDSSM-II (ensemble)Accuracy78.3Unverified
3BERT-large 340MAccuracy78.3Unverified
4UDSSM-I (ensemble)Accuracy76.7Unverified
5DSSMAccuracy75Unverified
6UDSSM-IIAccuracy75Unverified
7BERT-base 110M + MASAccuracy68.3Unverified
8USSM + Supervised Deepnet + 3 Knowledge BasesAccuracy66.7Unverified
9Word-level CNN+LSTM (full scoring)Accuracy60Unverified
10Subword-level Transformer LMAccuracy58.3Unverified
#ModelMetricClaimedVerifiedStatus
1BERT (pred POS/lemmas)Tags (Full) Acc82.5Unverified
2BERT (none)Tags (Full) Acc82Unverified
3BERT (gold POS/lemmas)Tags (Full) Acc81Unverified
4GloVe (gold POS/lemmas)Tags (Full) Acc79.3Unverified
5RoBERTa + LinearFull F1 (Preps)78.2Unverified
6GloVe (none)Tags (Full) Acc77.5Unverified
7GloVe (pred POS/lemmas)Tags (Full) Acc77.1Unverified
8SVM (feature-rich, gold syntax)Role F1 (Preps)62.2Unverified
9BiLSTM + MLP (gold syntax)Role F1 (Preps)62.2Unverified
10SVM (feature-rich, auto syntax)Role F1 (Preps)58.2Unverified
#ModelMetricClaimedVerifiedStatus
1CaseLaw-BERTCaseHOLD75.6Unverified
2Legal-BERTCaseHOLD75.1Unverified
3DeBERTaCaseHOLD72.1Unverified
4LongformerCaseHOLD72Unverified
5RoBERTaCaseHOLD71.7Unverified
6BERTCaseHOLD70.7Unverified
7BigBirdCaseHOLD70.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConvBERT-DGAverage74.6Unverified
2ConvBERT-DG + Pre + MultiAverage73.8Unverified
3mslmAverage73.49Unverified
4ConvBERT + Pre + MultiAverage68.22Unverified
5BanLanGenAverage39.16Unverified
#ModelMetricClaimedVerifiedStatus
1ConvBERT + Pre + MultiAverage86.89Unverified
2mslmAverage85.83Unverified
3ConvBERT-DG + Pre + MultiAverage85.34Unverified
#ModelMetricClaimedVerifiedStatus
1MT-DNN-SMARTAverage89.9Unverified
2BERT-LARGEAverage82.1Unverified