Interpretation of NLP models through input marginalization

Interpretation of NLP models through input marginalization

27 October 2020

Papers citing "Interpretation of NLP models through input marginalization"

18 / 18 papers shown

Title
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Models Sepehr Kamahi Yadollah Yaghoobzadeh 55 0 0 21 Aug 2024
InfFeed: Influence Functions as a Feedback to Improve the Performance of Subjective Tasks Somnath Banerjee Maulindu Sarkar Punyajoy Saha Binny Mathew Animesh Mukherjee TDI 36 0 0 22 Feb 2024
Interpreting Sentiment Composition with Latent Semantic Tree Zhongtao Jiang Yuanzhe Zhang Cao Liu Jiansong Chen Jun Zhao Kang Liu CoGe 31 0 0 31 Aug 2023
A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text Classification Xiang Hu Xinyu Kong Kewei Tu MILM BDL 34 5 0 06 Mar 2023
BMX: Boosting Natural Language Generation Metrics with Explainability Christoph Leiter Hoang-Quan Nguyen Steffen Eger ELM 24 0 0 20 Dec 2022
How explainable are adversarially-robust CNNs? Mehdi Nourelahi Lars Kotthoff Peijie Chen Anh Totti Nguyen AAML FAtt 24 8 0 25 May 2022
The Solvability of Interpretability Evaluation Metrics Yilun Zhou J. Shah 76 8 0 18 May 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection Esma Balkir I. Nejadgholi Kathleen C. Fraser S. Kiritchenko FAtt 41 27 0 06 May 2022
Learning to Scaffold: Optimizing Model Explanations for Teaching Patrick Fernandes Marcos Vinícius Treviso Danish Pruthi André F. T. Martins Graham Neubig FAtt 30 22 0 22 Apr 2022
Towards Explainable Evaluation Metrics for Natural Language Generation Christoph Leiter Piyawat Lertvittayakumjorn M. Fomicheva Wei Zhao Yang Gao Steffen Eger AAML ELM 30 20 0 21 Mar 2022
Deconfounding to Explanation Evaluation in Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xia Hu Fuli Feng Xiangnan He Tat-Seng Chua FAtt CML 17 14 0 21 Jan 2022
Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models? Thang M. Pham Trung H. Bui Long Mai Anh Totti Nguyen 21 7 0 22 Oct 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
Jointly Attacking Graph Neural Network and its Explanations Wenqi Fan Wei Jin Xiaorui Liu Han Xu Xianfeng Tang Suhang Wang Qing Li Jiliang Tang Jianping Wang Charu C. Aggarwal AAML 42 28 0 07 Aug 2021
On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation Wei Zhang Ziming Huang Yada Zhu Guangnan Ye Xiaodong Cui Fan Zhang 31 17 0 09 Jun 2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations Peter Hase Harry Xie Joey Tianyi Zhou OODD LRM FAtt 29 91 0 01 Jun 2021
Flexible Instance-Specific Rationalization of NLP Models G. Chrysostomou Nikolaos Aletras 31 14 0 16 Apr 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 44 95 0 02 Mar 2021