activity
20202022
most citedInterpreting Deep Learning Models in Natural Language Processing: A Review

25 citations · 44 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG20221 cited

Granular-Ball Fuzzy Set and Its Implementation in SVM

Shuyin Xia, Xiaoyu Lian, Guoyin Wang +2

Most existing fuzzy set methods use points as their input, which is the finest granularity from the perspective of granular computing. Consequently, these methods are neither effic…

cs.CV20211 cited

Rethinking the Image Feature Biases Exhibited by Deep CNN Models

Dawei Dai, Yutang Li, Huanan Bao +3

In recent years, convolutional neural networks (CNNs) have been applied successfully in many fields. However, such deep neural models are still regarded as black box in most tasks.…

cs.CL202125 cited

Interpreting Deep Learning Models in Natural Language Processing: A Review

Xiaofei Sun, Diyi Yang, Xiaoya Li +6

Neural network models have achieved state-of-the-art performances in a wide range of natural language processing (NLP) tasks. However, a long-standing criticism against neural netw…

cs.CL2021

Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken Language Understanding

Joo-Kyung Kim, Guoyin Wang, Sungjin Lee +1

A large-scale conversational agent can suffer from understanding user utterances with various ambiguities such as ASR ambiguity, intent ambiguity, and hypothesis ambiguity. When am…

cs.CL20212 cited

AUGNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation

Xinnuo Xu, Guoyin Wang, Young-Bum Kim +1

Natural Language Generation (NLG) is a key component in a task-oriented dialogue system, which converts the structured meaning representation (MR) to the natural language. For larg…

cs.AI2020

LRA: an accelerated rough set framework based on local redundancy of attribute for feature selection

Shuyin Xia, Wenhua Li, Guoyin Wang +3

In this paper, we propose and prove the theorem regarding the stability of attributes in a decision system. Based on the theorem, we propose the LRA framework for accelerating roug…