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20182023
most citedUncertainty in Natural Language Processing: Sources, Quantification, and Applications

12 citations · 19 across the 9 of their papers we have counts for

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10 papers · 1 filter

cs.CL202312 cited

Uncertainty in Natural Language Processing: Sources, Quantification, and Applications

Mengting Hu, Zhen Zhang, Shiwan Zhao +2

As a main field of artificial intelligence, natural language processing (NLP) has achieved remarkable success via deep neural networks. Plenty of NLP tasks have been addressed in a…

cs.CL2023

Uncertainty-Aware Unlikelihood Learning Improves Generative Aspect Sentiment Quad Prediction

Mengting Hu, Yinhao Bai, Yike Wu +5

Recently, aspect sentiment quad prediction has received widespread attention in the field of aspect-based sentiment analysis. Existing studies extract quadruplets via pre-trained g…

cs.CL2023

E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition

Zhen Zhang, Mengting Hu, Shiwan Zhao +6

Most named entity recognition (NER) systems focus on improving model performance, ignoring the need to quantify model uncertainty, which is critical to the reliability of NER syste…

cs.CL20222 cited

Improving Aspect Sentiment Quad Prediction via Template-Order Data Augmentation

Mengting Hu, Yike Wu, Hang Gao +2

Recently, aspect sentiment quad prediction (ASQP) has become a popular task in the field of aspect-level sentiment analysis. Previous work utilizes a predefined template to paraphr…

cs.CL2021

Efficient Mind-Map Generation via Sequence-to-Graph and Reinforced Graph Refinement

Mengting Hu, Honglei Guo, Shiwan Zhao +2

A mind-map is a diagram that represents the central concept and key ideas in a hierarchical way. Converting plain text into a mind-map will reveal its key semantic structure and be…

cs.CL20212 cited

Multi-Label Few-Shot Learning for Aspect Category Detection

Mengting Hu, Shiwan Zhao, Honglei Guo +5

Aspect category detection (ACD) in sentiment analysis aims to identify the aspect categories mentioned in a sentence. In this paper, we formulate ACD in the few-shot learning scena…