Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs

16 January 2018

Papers citing "Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs"

50 / 54 papers shown

Title
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions Fabian Fumagalli Maximilian Muschalik Patrick Kolpaczki Eyke Hüllermeier Barbara Hammer 43 6 0 17 May 2024
Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models Antoine Louis Gijs van Dijck Gerasimos Spanakis ELM AILaw 30 35 0 29 Sep 2023
Single-Class Target-Specific Attack against Interpretable Deep Learning Systems Eldor Abdukhamidov Mohammed Abuhamad George K. Thiruvathukal Hyoungshick Kim Tamer Abuhmed AAML 27 2 0 12 Jul 2023
A semantically enhanced dual encoder for aspect sentiment triplet extraction Baoxing Jiang Shehui Liang Peiyu Liu Kaifang Dong Hongye Li 27 15 0 14 Jun 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 30 22 0 22 May 2023
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 34 6 0 25 Mar 2023
Does a Neural Network Really Encode Symbolic Concepts? Mingjie Li Quanshi Zhang 29 30 0 25 Feb 2023
Relational Local Explanations V. Borisov Gjergji Kasneci FAtt 22 0 0 23 Dec 2022
Generating Hierarchical Explanations on Text Classification Without Connecting Rules Yiming Ju Yuanzhe Zhang Kang Liu Jun Zhao FAtt 26 3 0 24 Oct 2022
Feature Importance for Time Series Data: Improving KernelSHAP M. Villani J. Lockhart Daniele Magazzeni FAtt AI4TS 40 6 0 05 Oct 2022
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation Reduan Achtibat Maximilian Dreyer Ilona Eisenbraun S. Bosse Thomas Wiegand Wojciech Samek Sebastian Lapuschkin FAtt 36 134 0 07 Jun 2022
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP Lijie Wang Yaozong Shen Shu-ping Peng Shuai Zhang Xinyan Xiao Hao Liu Hongxuan Tang Ying-Cong Chen Hua Wu Haifeng Wang ELM 19 21 0 23 May 2022
FaiRR: Faithful and Robust Deductive Reasoning over Natural Language Soumya Sanyal Harman Singh Xiang Ren ReLM LRM 32 45 0 19 Mar 2022
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement Xiaoting Shao Karl Stelzner Kristian Kersting CML DRL 29 3 0 01 Feb 2022
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 44 55 0 05 Dec 2021
Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives Ziyi Liu Jiaqi Zhang Yongshuai Hou Xinran Zhang Ge Li Yang Xiang 19 14 0 09 Nov 2021
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 19 45 0 20 Oct 2021
Discretized Integrated Gradients for Explaining Language Models Soumya Sanyal Xiang Ren FAtt 17 53 0 31 Aug 2021
Neuron-level Interpretation of Deep NLP Models: A Survey Hassan Sajjad Nadir Durrani Fahim Dalvi MILM AI4CE 35 82 0 30 Aug 2021
Shapley Explanation Networks Rui Wang Xiaoqian Wang David I. Inouye TDI FAtt 27 44 0 06 Apr 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin Eric Wang Meng Zhou Jie Shi Quanshi Zhang AAML 72 22 0 12 Mar 2021
On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification Alejandro Barredo Arrieta S. Gil-Lopez I. Laña Miren Nekane Bilbao Javier Del Ser AI4TS 41 13 0 17 Feb 2021
Self-Explaining Structures Improve NLP Models Zijun Sun Chun Fan Qinghong Han Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li MILM XAI LRM FAtt 46 38 0 03 Dec 2020
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations Wolfgang Stammer P. Schramowski Kristian Kersting FAtt 14 107 0 25 Nov 2020
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification Linyi Yang Eoin M. Kenny T. L. J. Ng Yi Yang Barry Smyth Ruihai Dong 15 70 0 23 Oct 2020
A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Eric Wang Jie Ren Shuyu Lin Xiangming Zhu Yisen Wang Quanshi Zhang AAML 29 94 0 08 Oct 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 15 63 0 01 Oct 2020
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking M. Schlichtkrull Nicola De Cao Ivan Titov AI4CE 36 214 0 01 Oct 2020
Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance Mattia Carletti M. Terzi Gian Antonio Susto 36 42 0 21 Jul 2020
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection Michael Tsang Dehua Cheng Hanpeng Liu Xuening Feng Eric Zhou Yan Liu FAtt 24 60 0 19 Jun 2020
Contextualizing Hate Speech Classifiers with Post-hoc Explanation Brendan Kennedy Xisen Jin Aida Mostafazadeh Davani Morteza Dehghani Xiang Ren 22 138 0 05 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 43 371 0 30 Apr 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data B. Shickel Parisa Rashidi AI4TS 33 17 0 27 Apr 2020
How recurrent networks implement contextual processing in sentiment analysis Niru Maheswaranathan David Sussillo 22 22 0 17 Apr 2020
Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection Hanjie Chen Guangtao Zheng Yangfeng Ji FAtt 36 92 0 04 Apr 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 29 485 0 12 Feb 2020
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks Joseph D. Janizek Pascal Sturmfels Su-In Lee FAtt 30 143 0 10 Feb 2020
Explaining and Interpreting LSTMs L. Arras Jose A. Arjona-Medina Michael Widrich G. Montavon Michael Gillhofer K. Müller Sepp Hochreiter Wojciech Samek FAtt AI4TS 21 79 0 25 Sep 2019
Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment Jaap Jumelet Willem H. Zuidema Dieuwke Hupkes LRM 33 37 0 19 Sep 2019
Interpretable and Steerable Sequence Learning via Prototypes Yao Ming Panpan Xu Huamin Qu Liu Ren AI4TS 12 138 0 23 Jul 2019
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics Niru Maheswaranathan Alex H. Williams Matthew D. Golub Surya Ganguli David Sussillo 26 78 0 25 Jun 2019
Incorporating Priors with Feature Attribution on Text Classification Frederick Liu Besim Avci FAtt FaML 33 120 0 19 Jun 2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data Tian Guo Tao R. Lin Nino Antulov-Fantulin AI4TS 26 154 0 28 May 2019
Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees Summer Devlin Chandan Singh W. James Murdoch Bin Yu FAtt 19 14 0 18 May 2019
Veridical Data Science Bin Yu Karl Kumbier 23 162 0 23 Jan 2019
Interpretable machine learning: definitions, methods, and applications W. James Murdoch Chandan Singh Karl Kumbier R. Abbasi-Asl Bin-Xia Yu XAI HAI 49 1,421 0 14 Jan 2019
Can I trust you more? Model-Agnostic Hierarchical Explanations Michael Tsang Youbang Sun Dongxu Ren Yan Liu FAtt 16 25 0 12 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 30 169 0 03 Dec 2018
What made you do this? Understanding black-box decisions with sufficient input subsets Brandon Carter Jonas W. Mueller Siddhartha Jain David K Gifford FAtt 39 77 0 09 Oct 2018
Interpreting Neural Networks With Nearest Neighbors Eric Wallace Shi Feng Jordan L. Boyd-Graber AAML FAtt MILM 20 53 0 08 Sep 2018