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

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Showing 851–900 of 1978 papers

TitleStatusHype
Improving BERT with Hybrid Pooling Network and Drop Mask—0
Natural Language Instructions for Intuitive Human Interaction with Robotic Assistants in Field Construction Work—0
Teach Me How to Learn: A Perspective Review towards User-centered Neuro-symbolic Learning for Robotic Surgical Systems—0
Enhancing LLM with Evolutionary Fine Tuning for News Summary Generation—0
In-Context Learning for Attention Scheme: from Single Softmax Regression to Multiple Softmax Regression via a Tensor Trick—0
HeGeL: A Novel Dataset for Geo-Location from Hebrew TextCode0
Revisiting Sample Size Determination in Natural Language UnderstandingCode0
A negation detection assessment of GPTs: analysis with the xNot360 dataset—0
SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills—0
Federated Self-Learning with Weak Supervision for Speech Recognition—0
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation—0
Surfer: Progressive Reasoning with World Models for Robotic Manipulation—0
Adversarial Robustness of Prompt-based Few-Shot Learning for Natural Language UnderstandingCode0
Multilingual Few-Shot Learning via Language Model Retrieval—0
Data Selection for Fine-tuning Large Language Models Using Transferred Shapley ValuesCode0
Bridging the Gap between Decision and Logits in Decision-based Knowledge Distillation for Pre-trained Language ModelsCode0
Deep Model Compression Also Helps Models Capture AmbiguityCode0
Multimodal Audio-textual Architecture for Robust Spoken Language Understanding—0
On the N-gram Approximation of Pre-trained Language Models—0
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image UnderstandingCode0
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding—0
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-trainingCode0
LogiQA 2.0—An Improved Dataset for Logical Reasoning in Natural Language UnderstandingCode0
bgGLUE: A Bulgarian General Language Understanding Evaluation BenchmarkCode0
A Simple yet Effective Self-Debiasing Framework for Transformer ModelsCode0
Automatic Glossary of Clinical Terminology: a Large-Scale Dictionary of Biomedical Definitions Generated from Ontological Knowledge—0
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training QuantizationCode0
Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home—0
Quantization-Aware and Tensor-Compressed Training of Transformers for Natural Language Understanding—0
A template-independent approach for information extraction in real estate documentsCode0
Tri-level Joint Natural Language Understanding for Multi-turn Conversational DatasetsCode0
Robust Natural Language Understanding with Residual Attention DebiasingCode0
A Unified Framework for Slot based Response Generation in a Multimodal Dialogue SystemCode0
MERGE: Fast Private Text GenerationCode0
Universal Self-Adaptive Prompting—0
Large Language Models for User Interest Journeys—0
GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP—0
Exploring Affordance and Situated Meaning in Image Captions: A Multimodal Analysis—0
Prompting Large Language Models for Counterfactual Generation: An Empirical Study—0
On Degrees of Freedom in Defining and Testing Natural Language Understanding—0
Don't Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMs—0
Bi-Drop: Enhancing Fine-tuning Generalization via Synchronous sub-net Estimation and Optimization—0
DialogVCS: Robust Natural Language Understanding in Dialogue System Upgrade—0
Do prompt positions really matter?Code0
mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinations—0
mPMR: A Multilingual Pre-trained Machine Reader at ScaleCode0
Continual Dialogue State Tracking via Example-Guided Question AnsweringCode0
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding—0
From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding—0
Can Large Language Models Capture Dissenting Human Voices?Code0
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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