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

12 citations · 31 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CL2023★ 12 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.CL2022★ 2 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.LG2022

Classical Sequence Match is a Competitive Few-Shot One-Class Learner

Mengting Hu, Hang Gao, Yinhao Bai +1

Nowadays, transformer-based models gradually become the default choice for artificial intelligence pioneers. The models also show superiority even in the few-shot scenarios. In thi…

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.CL2021★ 2 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…

cs.CL2021

Hierarchical Ranking for Answer Selection

Hang Gao, Mengting Hu, Renhong Cheng +1

Answer selection is a task to choose the positive answers from a pool of candidate answers for a given question. In this paper, we propose a novel strategy for answer selection, ca…

cs.CL2019★ 3 cited

Learning to Detect Opinion Snippet for Aspect-Based Sentiment Analysis

Mengting Hu, Shiwan Zhao, Honglei Guo +2

Aspect-based sentiment analysis (ABSA) is to predict the sentiment polarity towards a particular aspect in a sentence. Recently, this task has been widely addressed by the neural a…

cs.CL2019★ 2 cited

Domain-Invariant Feature Distillation for Cross-Domain Sentiment Classification

Mengting Hu, Yike Wu, Shiwan Zhao +3

Cross-domain sentiment classification has drawn much attention in recent years. Most existing approaches focus on learning domain-invariant representations in both the source and t…

cs.CL2018★ 10 cited

CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis

Mengting Hu, Shiwan Zhao, Li Zhang +4

Aspect level sentiment classification is a fine-grained sentiment analysis task. To detect the sentiment towards a particular aspect in a sentence, previous studies have developed…