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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 451–500 of 1978 papers

TitleStatusHype
Self Generated Wargame AI: Double Layer Agent Task Planning Based on Large Language Model—0
Summarization-based Data Augmentation for Document ClassificationCode0
TaskWeaver: A Code-First Agent FrameworkCode5
Exploring the Robustness of Model-Graded Evaluations and Automated Interpretability—0
Explore the Potential of LLMs in Misinformation Detection: An Empirical Study—0
MultiLoRA: Democratizing LoRA for Better Multi-Task Learning—0
You don't need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric InstrumentsCode0
Effective Large Language Model Adaptation for Improved Grounding and Citation Generation—0
SQATIN: Supervised Instruction Tuning Meets Question Answering for Improved Dialogue NLUCode0
XplainLLM: A Knowledge-Augmented Dataset for Reliable Grounded Explanations in LLMsCode1
MAVEN-Arg: Completing the Puzzle of All-in-One Event Understanding Dataset with Event Argument AnnotationCode1
Fusion-Eval: Integrating Assistant Evaluators with LLMs—0
On the Calibration of Multilingual Question Answering LLMs—0
Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning—0
Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding—0
Conic10K: A Challenging Math Problem Understanding and Reasoning DatasetCode1
DACBERT: Leveraging Dependency Agreement for Cost-Efficient Bert Pretraining—0
RankAug: Augmented data ranking for text classification—0
Relation Extraction Model Based on Semantic Enhancement Mechanism—0
A Systematic Review of Deep Graph Neural Networks: Challenges, Classification, Architectures, Applications & Potential Utility in Bioinformatics—0
MARRS: Multimodal Reference Resolution System—0
Automatic Disfluency Detection from Untranscribed SpeechCode1
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy InstructionsCode1
IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models—0
Dense Retrieval as Indirect Supervision for Large-space Decision MakingCode0
TLM: Token-Level Masking for TransformersCode0
Large-scale Foundation Models and Generative AI for BigData Neuroscience—0
Evaluation of large language models using an Indian language LGBTI+ lexicon—0
Meaning and understanding in large language models—0
Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition ErrorsCode0
tagE: Enabling an Embodied Agent to Understand Human InstructionsCode0
Large Language Models are Temporal and Causal Reasoners for Video Question AnsweringCode1
Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language UnderstandingCode1
CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU TasksCode0
Primacy Effect of ChatGPTCode0
Explaining Interactions Between Text SpansCode0
StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical UnderstandingCode0
Chain-of-Thought Tuning: Masked Language Models can also Think Step By Step in Natural Language Understanding—0
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs—0
Reflection-Tuning: Data Recycling Improves LLM Instruction-TuningCode2
Core Building Blocks: Next Gen Geo Spatial GPT Application—0
Towards Automatic Satellite Images Captions Generation Using Large Language Models—0
Rethinking Relation Classification with Graph Meaning Representations—0
Empirical study of pretrained multilingual language models for zero-shot cross-lingual knowledge transfer in generation—0
GLoRE: Evaluating Logical Reasoning of Large Language ModelsCode1
Developing a Natural Language Understanding Model to Characterize Cable News Bias—0
Split-and-Denoise: Protect large language model inference with local differential privacyCode1
Evaluating The Effectiveness of Capsule Neural Network in Toxic Comment Classification using Pre-trained BERT EmbeddingsCode0
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language ModelsCode2
PHALM: Building a Knowledge Graph from Scratch by Prompting Humans and a Language ModelCode1
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All datasetsPDP60STREUSLELexGLUEDialoGLUE fewshotDialoGLUE fullGLUE

Benchmark Results

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