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 951975 of 1978 papers

TitleStatusHype
Integrating Heuristics and Learning in a Computational Architecture for Cognitive Trading0
Integrating Large Language Models with Graphical Session-Based Recommendation0
ICH-Qwen: A Large Language Model Towards Chinese Intangible Cultural Heritage0
Task-specific Compression for Multi-task Language Models using Attribution-based Pruning0
IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models0
Core Building Blocks: Next Gen Geo Spatial GPT Application0
COREALMLIB: An ALM Library Translated from the Component Library0
Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification0
A Deep Learning System for Domain-specific Speech Recognition0
A Cohesive Distillation Architecture for Neural Language Models0
HyperPrompt: Prompt-based Task-Conditioning of Transformers0
Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?0
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding0
CopyBERT: A Unified Approach to Question Generation with Self-Attention0
Hypernymy Detection for Low-Resource Languages via Meta Learning0
Investigating Inner Properties of Multimodal Representation and Semantic Compositionality with Brain-based Componential Semantics0
Convo: What does conversational programming need? An exploration of machine learning interface design0
HyperGrid Transformers: Towards A Single Model for Multiple Tasks0
HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections0
Hyperbolic Deep Learning for Chinese Natural Language Understanding0
Hybrid MemNet for Extractive Summarization0
Convex Polytope Modelling for Unsupervised Derivation of Semantic Structure for Data-efficient Natural Language Understanding0
Attentive Contextual Carryover for Multi-Turn End-to-End Spoken Language Understanding0
Human-like Cognitive Generalization for Large Models via Brain-in-the-loop Supervision0
Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systems0
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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