972 citations · 1.2k across the 31 of their papers we have counts for
18 papers · 1 filter
Towards Faithful Explanations for Text Classification with Robustness Improvement and Explanation Guided Training
Dongfang Li, Baotian Hu, Qingcai Chen +1
Feature attribution methods highlight the important input tokens as explanations to model predictions, which have been widely applied to deep neural networks towards trustworthy AI…
A Neural Span-Based Continual Named Entity Recognition Model
Yunan Zhang, Qingcai Chen
Named Entity Recognition (NER) models capable of Continual Learning (CL) are realistically valuable in areas where entity types continuously increase (e.g., personal assistants). M…
Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates
Dongfang Li, Baotian Hu, Qingcai Chen
Calibration strengthens the trustworthiness of black-box models by producing better accurate confidence estimates on given examples. However, little is known about if model explana…
Prompt-based Text Entailment for Low-Resource Named Entity Recognition
Dongfang Li, Baotian Hu, Qingcai Chen
Pre-trained Language Models (PLMs) have been applied in NLP tasks and achieve promising results. Nevertheless, the fine-tuning procedure needs labeled data of the target domain, ma…
A Survey on Table Question Answering: Recent Advances
Nengzheng Jin, Joanna Siebert, Dongfang Li +1
Table Question Answering (Table QA) refers to providing precise answers from tables to answer a user's question. In recent years, there have been a lot of works on table QA, but th…
Unifying Model Explainability and Robustness for Joint Text Classification and Rationale Extraction
Dongfang Li, Baotian Hu, Qingcai Chen +3
Recent works have shown explainability and robustness are two crucial ingredients of trustworthy and reliable text classification. However, previous works usually address one of tw…
Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning
Shuoran Jiang, Qingcai Chen, Xin Liu +2
Graph convolutional network (GCN) has become popular in various natural language processing (NLP) tasks with its superiority in long-term and non-consecutive word interactions. How…
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Ningyu Zhang, Mosha Chen, Zhen Bi +20
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice. With the development of biomedical langua…
You Can Do Better! If You Elaborate the Reason When Making Prediction
Dongfang Li, Jingcong Tao, Qingcai Chen +1
Neural predictive models have achieved remarkable performance improvements in various natural language processing tasks. However, most neural predictive models suffer from the lack…
A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews
Kai Chen, Meng Niu, Qingcai Chen
We address the task of automatically scoring the competency of candidates based on textual features, from the automatic speech recognition (ASR) transcriptions in the asynchronous…
Neural Data-to-Text Generation with Dynamic Content Planning
Kai Chen, Fayuan Li, Baotian Hu +3
Neural data-to-text generation models have achieved significant advancement in recent years. However, these models have two shortcomings: the generated texts tend to miss some vita…
Decomposing Word Embedding with the Capsule Network
Xin Liu, Qingcai Chen, Yan Liu +4
Word sense disambiguation tries to learn the appropriate sense of an ambiguous word in a given context. The existing pre-trained language methods and the methods based on multi-emb…
Semi-supervised Visual Feature Integration for Pre-trained Language Models
Lisai Zhang, Qingcai Chen, Dongfang Li +1
Integrating visual features has been proved useful for natural language understanding tasks. Nevertheless, in most existing multimodal language models, the alignment of visual and…
BERTSel: Answer Selection with Pre-trained Models
Dongfang Li, Yifei Yu, Qingcai Chen +1
Recently, pre-trained models have been the dominant paradigm in natural language processing. They achieved remarkable state-of-the-art performance across a wide range of related ta…
Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering
Xiaoqiang Zhou, Baotian Hu, Qingcai Chen +2
In this paper, the answer selection problem in community question answering (CQA) is regarded as an answer sequence labeling task, and a novel approach is proposed based on the rec…
LCSTS: A Large Scale Chinese Short Text Summarization Dataset
Baotian Hu, Qingcai Chen, Fangze Zhu
Automatic text summarization is widely regarded as the highly difficult problem, partially because of the lack of large text summarization data set. Due to the great challenge of c…
Convolutional Neural Network Architectures for Matching Natural Language Sentences
Baotian Hu, Zhengdong Lu, Hang Li +1
Semantic matching is of central importance to many natural language tasks \cite{bordes2014semantic,RetrievalQA}. A successful matching algorithm needs to adequately model the inter…
Context-Dependent Translation Selection Using Convolutional Neural Network
Zhaopeng Tu, Baotian Hu, Zhengdong Lu +1
We propose a novel method for translation selection in statistical machine translation, in which a convolutional neural network is employed to judge the similarity between a phrase…