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 251275 of 1978 papers

TitleStatusHype
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization ApproachCode1
On Transferability of Prompt Tuning for Natural Language ProcessingCode1
End-to-End Slot Alignment and Recognition for Cross-Lingual NLUCode1
On the Importance of Effectively Adapting Pretrained Language Models for Active LearningCode1
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language UnderstandingCode1
Fact-level Extractive Summarization with Hierarchical Graph Mask on BERTCode1
A Generative Model for Joint Natural Language Understanding and GenerationCode1
FastFormers: Highly Efficient Transformer Models for Natural Language UnderstandingCode1
Exploring the State of the Art in Legal QA SystemsCode1
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring SystemsCode1
Extracting Event Temporal Relations via Hyperbolic GeometryCode1
FaVIQ: FAct Verification from Information-seeking QuestionsCode1
FlipDA: Effective and Robust Data Augmentation for Few-Shot LearningCode1
Bridging Text and Vision: A Multi-View Text-Vision Registration Approach for Cross-Modal Place RecognitionCode1
Beyond Autoregression: Fast LLMs via Self-Distillation Through TimeCode1
Event Time Extraction and Propagation via Graph Attention NetworksCode1
Break, Perturb, Build: Automatic Perturbation of Reasoning Paths Through Question DecompositionCode1
Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM FamilyCode1
Evolving Attention with Residual ConvolutionsCode1
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksCode1
Ape210K: A Large-Scale and Template-Rich Dataset of Math Word ProblemsCode1
Call for Papers -- The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpusCode1
A Persian Benchmark for Joint Intent Detection and Slot FillingCode1
Explaining Patterns in Data with Language Models via Interpretable AutopromptingCode1
Evaluating Scoped Meaning RepresentationsCode1
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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