Understanding Convolutional Neural Networks for Text Classification

21 September 2018

Papers citing "Understanding Convolutional Neural Networks for Text Classification"

21 / 21 papers shown

Title
DepressionX: Knowledge Infused Residual Attention for Explainable Depression Severity Assessment Yusif Ibrahimov Tarique Anwar Tommy Yuan 44 0 0 28 Jan 2025
Explainability of machine learning approaches in forensic linguistics: a case study in geolinguistic authorship profiling Dana Roemling Yves Scherrer Aleksandra Miletic 53 0 0 29 Apr 2024
Continual Graph Convolutional Network for Text Classification Tiandeng Wu Qijiong Liu Yinhao Cao yao. huang Xiao-Ming Wu Jiandong Ding GNN 21 10 0 09 Apr 2023
Explainable AI for Bioinformatics: Methods, Tools, and Applications Md. Rezaul Karim Tanhim Islam Oya Beyan Christoph Lange Michael Cochez Dietrich-Rebholz Schuhmann Stefan Decker 29 68 0 25 Dec 2022
StyLEx: Explaining Style Using Human Lexical Annotations Shirley Anugrah Hayati Kyumin Park Dheeraj Rajagopal Lyle Ungar Dongyeop Kang 25 3 0 14 Oct 2022
TextConvoNet:A Convolutional Neural Network based Architecture for Text Classification Sanskar Soni S. Chouhan S. Rathore 33 95 0 10 Mar 2022
GADoT: GAN-based Adversarial Training for Robust DDoS Attack Detection Maged AbdelAty Sandra Scott-Hayward Roberto Doriguzzi-Corin Domenico Siracusa AAML 21 23 0 31 Jan 2022
Robustness Tests of NLP Machine Learning Models: Search and Semantically Replace Rahul Singh Karan Jindal Yufei Yu Hanyu Yang Tarun Joshi Matthew A. Campbell Wayne B. Shoumaker 50 2 0 20 Apr 2021
Structural block driven - enhanced convolutional neural representation for relation extraction Dongsheng Wang Prayag Tiwari S. Garg Hongyin Zhu P. Bruza NAI AI4TS 27 21 0 21 Mar 2021
Transformer Feed-Forward Layers Are Key-Value Memories Mor Geva R. Schuster Jonathan Berant Omer Levy KELM 27 741 0 29 Dec 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 13 62 0 01 Oct 2020
When will the mist clear? On the Interpretability of Machine Learning for Medical Applications: a survey A. Banegas-Luna Jorge Pena-García Adrian Iftene F. Guadagni P. Ferroni Noemi Scarpato Fabio Massimo Zanzotto A. Bueno-Crespo Horacio Pérez-Sánchez OOD 13 1 0 01 Oct 2020
SHAP values for Explaining CNN-based Text Classification Models Wei Zhao Tarun Joshi V. Nair Agus Sudjianto FAtt 12 36 0 26 Aug 2020
Explainable CNN-attention Networks (C-Attention Network) for Automated Detection of Alzheimer's Disease Ning Wang Mingxuan Chen K. P. Subbalakshmi 20 22 0 25 Jun 2020
Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection Hanjie Chen Guangtao Zheng Yangfeng Ji FAtt 36 91 0 04 Apr 2020
Linking Social Media Posts to News with Siamese Transformers Jacob Danovitch 24 2 0 10 Jan 2020
A Framework for Explainable Text Classification in Legal Document Review Christian J. Mahoney Jianping Zhang Nathaniel Huber-Fliflet Peter Gronvall Haozhen Zhao AILaw 14 32 0 19 Dec 2019
Detecting Local Insights from Global Labels: Supervised & Zero-Shot Sequence Labeling via a Convolutional Decomposition A. Schmaltz 19 8 0 04 Jun 2019
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 229 201 0 06 Jul 2017
Symbolic, Distributed and Distributional Representations for Natural Language Processing in the Era of Deep Learning: a Survey L. Ferrone Fabio Massimo Zanzotto 34 37 0 02 Feb 2017
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 255 13,364 0 25 Aug 2014