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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 1701–1750 of 1978 papers

TitleStatusHype
Improving Classification-Based Natural Language Understanding with Non-Expert Annotation—0
Improving Commonsense Contingent Reasoning by Pseudo-data and Its Application to the Related Tasks—0
Improving Commonsense Question Answering by Graph-based Iterative Retrieval over Multiple Knowledge Sources—0
Improving Event Temporal Relation Classification via Auxiliary Label-Aware Contrastive Learning—0
Improving Multimodal Large Language Models Using Continual Learning—0
Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding—0
Improving Natural Language Understanding by Reverse Mapping Bytepair Encoding—0
Improving Romanian BioNER Using a Biologically Inspired System—0
Improving Small-Scale Large Language Models Function Calling for Reasoning Tasks—0
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses—0
Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives—0
Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning—0
Improving Tokenisation by Alternative Treatment of Spaces—0
In-Context Learning for Attention Scheme: from Single Softmax Regression to Multiple Softmax Regression via a Tensor Trick—0
Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking—0
Incorporating Syntax and Frame Semantics in Neural Network for Machine Reading Comprehension—0
Incrementalizing RASA's Open-Source Natural Language Understanding Pipeline—0
RNN based Incremental Online Spoken Language Understanding—0
Incremental processing of noisy user utterances in the spoken language understanding task—0
Making Task-Oriented Dialogue Datasets More Natural by Synthetically Generating Indirect User Requests—0
INDUS: Effective and Efficient Language Models for Scientific Applications—0
Industry Scale Semi-Supervised Learning for Natural Language Understanding—0
Inference Annotation of a Chinese Corpus for Opinion Mining—0
Inferring Compact Representations for Efficient Natural Language Understanding of Robot Instructions—0
InFoBERT: Zero-Shot Approach to Natural Language Understanding Using Contextualized Word Embedding—0
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding—0
Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models—0
Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home—0
Inspecting the concept knowledge graph encoded by modern language models—0
Integrated Learning of Dialog Strategies and Semantic Parsing—0
Semi-supervised Visual Feature Integration for Pre-trained Language Models—0
Integrating Heuristics and Learning in a Computational Architecture for Cognitive Trading—0
Integrating Large Language Models with Graphical Session-Based Recommendation—0
Intelligent Assistant Language Understanding On Device—0
Intent Generation for Goal-Oriented Dialogue Systems based on Schema.org Annotations—0
Intent Matching based Customer Services Chatbot with Natural Language Understanding—0
Intent Recognition and Unsupervised Slot Identification for Low Resourced Spoken Dialog Systems—0
Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?—0
Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?—0
InternalInspector I^2: Robust Confidence Estimation in LLMs through Internal States—0
Introducing the Talk Markup Language (TalkML):Adding a little social intelligence to industrial speech interfaces—0
Investigating Inner Properties of Multimodal Representation and Semantic Compositionality with Brain-based Componential Semantics—0
Investigating LLMs as Voting Assistants via Contextual Augmentation: A Case Study on the European Parliament Elections 2024—0
Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks—0
Not Cheating on the Turing Test: Towards Grounded Language Learning in Artificial Intelligence—0
Is Knowledge Embedding Fully Exploited in Language Understanding? An Empirical Study—0
Is Language Modeling Enough? Evaluating Effective Embedding Combinations—0
Is Supervised Syntactic Parsing Beneficial for Language Understanding Tasks? An Empirical Investigation—0
Jailbreaking and Mitigation of Vulnerabilities in Large Language Models—0
Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer—0
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All datasetsPDP60STREUSLELexGLUEDialoGLUE fewshotDialoGLUE fullGLUE

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HNNAccuracy90—Unverified
2BERT-large 340MAccuracy78.3—Unverified
3UDSSM-II (ensemble)Accuracy78.3—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