Improving Deep Learning Interpretability by Saliency Guided Training

29 November 2021

Aya Abdelsalam Ismail

Papers citing "Improving Deep Learning Interpretability by Saliency Guided Training"

43 / 43 papers shown

Title
Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detection Ruoyu Chen Hua Zhang Jingzhi Li Li Liu Zhen Huang Xiaochun Cao 32 0 0 09 Apr 2025
Time-series attribution maps with regularized contrastive learning Steffen Schneider Rodrigo González Laiz Anastasiia Filippova Markus Frey Mackenzie W. Mathis BDL FAtt CML AI4TS 73 0 0 17 Feb 2025
Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task Alireza Maleki Mahsa Lavaei Mohsen Bagheritabar Salar Beigzad Zahra Abadi MQ 62 0 0 05 Dec 2024
ConLUX: Concept-Based Local Unified Explanations Junhao Liu Haonan Yu Xin Zhang FAtt LRM 21 0 0 16 Oct 2024
The Overfocusing Bias of Convolutional Neural Networks: A Saliency-Guided Regularization Approach David Bertoin Eduardo Hugo Sanchez Mehdi Zouitine Emmanuel Rachelson 18 0 0 25 Sep 2024
Improving Network Interpretability via Explanation Consistency Evaluation Hefeng Wu Hao Jiang Keze Wang Ziyi Tang Xianghuan He Liang Lin FAtt AAML 21 0 0 08 Aug 2024
Explanation Regularisation through the Lens of Attributions Pedro Ferreira Wilker Aziz Ivan Titov 18 1 0 23 Jul 2024
Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach Amira Guesmi Nishant Suresh Aswani Muhammad Shafique FAtt AAML 19 1 0 10 May 2024
Explainable Interface for Human-Autonomy Teaming: A Survey Xiangqi Kong Yang Xing Antonios Tsourdos Ziyue Wang Weisi Guo Adolfo Perrusquía Andreas Wikander 30 3 0 04 May 2024
CA-Stream: Attention-based pooling for interpretable image recognition Felipe Torres Hanwei Zhang R. Sicre Stéphane Ayache Yannis Avrithis 36 0 0 23 Apr 2024
Bayesian Neural Networks with Domain Knowledge Priors Dylan Sam Rattana Pukdee Daniel P. Jeong Yewon Byun J. Zico Kolter BDL UQCV 22 9 0 20 Feb 2024
Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence C. Coglianese Colton R. Crum FaML 24 2 0 13 Feb 2024
Towards Faithful Explanations for Text Classification with Robustness Improvement and Explanation Guided Training Dongfang Li Baotian Hu Qingcai Chen Shan He 21 4 0 29 Dec 2023
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 12 2 0 09 Nov 2023
MENTOR: Human Perception-Guided Pretraining for Increased Generalization Colton R. Crum Adam Czajka 51 1 0 30 Oct 2023
REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization Mohammad Reza Ghasemi Madani Pasquale Minervini 12 4 0 22 Oct 2023
Make Your Decision Convincing! A Unified Two-Stage Framework: Self-Attribution and Decision-Making Yanrui Du Sendong Zhao Hao Wang Yuhan Chen Rui Bai Zewen Qiang Muzhen Cai Bing Qin 16 0 0 20 Oct 2023
Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers Yuya Yoshikawa Tomoharu Iwata 14 0 0 19 Oct 2023
SMOOT: Saliency Guided Mask Optimized Online Training Ali Karkehabadi Houman Homayoun Avesta Sasan AAML 16 16 0 01 Oct 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 74 7 0 14 Sep 2023
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities Munib Mesinovic Peter Watkinson Ting Zhu FaML 14 3 0 16 Aug 2023
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models Liang Zhang Nathaniel Xu Pengfei Yang Gao Jin Cheng-Chao Huang Lijun Zhang 18 8 0 11 Aug 2023
Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing Swastika Roy Hatim Chergui C. Verikoukis FedML 17 2 0 18 Jul 2023
Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations Tong Sun Yuyang Gao Shubham Khaladkar Sijia Liu Liang Zhao Younghoon Kim S. Hong AAML FAtt HAI 22 6 0 08 Jul 2023
Does Saliency-Based Training bring Robustness for Deep Neural Networks in Image Classification? Ali Karkehabadi FAtt AAML 6 0 0 28 Jun 2023
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency Owen Queen Thomas Hartvigsen Teddy Koker Huan He Theodoros Tsiligkaridis Marinka Zitnik AI4TS 37 16 0 03 Jun 2023
A Neural Emulator for Uncertainty Estimation of Fire Propagation Andrew Bolt Conrad Sanderson J. Dabrowski C. Huston Petra Kuhnert 11 3 0 10 May 2023
$On Pitfalls of $\textit{RemOve-And-Retrain}$: Data Processing Inequality Perspective$ On Pitfalls of $\textit{RemOve-And-Retrain}$ : Data Processing Inequality Perspective J. Song Keumgang Cha Junghoon Seo 27 2 0 26 Apr 2023
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 17 6 0 25 Mar 2023
Task-Adaptive Saliency Guidance for Exemplar-free Class Incremental Learning Xialei Liu Jiang-Tian Zhai Andrew D. Bagdanov Ke Li Mingg-Ming Cheng CLL 10 4 0 16 Dec 2022
Temporal Saliency Detection Towards Explainable Transformer-based Timeseries Forecasting Nghia Duong-Trung Kiran Madhusudhanan Danh Le-Phuoc AI4TS 30 4 0 15 Dec 2022
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Yuyang Gao Siyi Gu Junji Jiang S. Hong Dazhou Yu Liang Zhao 24 38 0 07 Dec 2022
Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods Nils Feldhus Leonhard Hennig Maximilian Dustin Nasert Christopher Ebert Robert Schwarzenberg Sebastian Möller FAtt 8 19 0 13 Oct 2022
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning David Bertoin Adil Zouitine Mehdi Zouitine Emmanuel Rachelson 12 17 0 16 Sep 2022
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System Xin Li Yao Qiang Chengyin Li Sijia Liu D. Zhu OOD MedIm 21 4 0 09 Sep 2022
Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators A. Watanabe Sara Ketabi Khashayar Namdar Namdar Farzad Khalvati 14 8 0 28 Jun 2022
VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives Zhuofan Ying Peter Hase Mohit Bansal LRM 15 13 0 22 Jun 2022
Core Risk Minimization using Salient ImageNet Sahil Singla Mazda Moayeri S. Feizi 12 14 0 28 Mar 2022
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement Leander Weber Sebastian Lapuschkin Alexander Binder Wojciech Samek 41 87 0 15 Mar 2022
UNIREX: A Unified Learning Framework for Language Model Rationale Extraction Aaron Chan Maziar Sanjabi Lambert Mathias L Tan Shaoliang Nie Xiaochang Peng Xiang Ren Hamed Firooz 14 41 0 16 Dec 2021
Feature Alignment as a Generative Process T. S. Farias Jonas Maziero DiffM BDL 12 1 0 23 Jun 2021
What went wrong and when? Instance-wise Feature Importance for Time-series Models S. Tonekaboni Shalmali Joshi Kieran Campbell D. Duvenaud Anna Goldenberg FAtt OOD AI4TS 44 14 0 05 Mar 2020
e-SNLI: Natural Language Inference with Natural Language Explanations Oana-Maria Camburu Tim Rocktaschel Thomas Lukasiewicz Phil Blunsom LRM 252 618 0 04 Dec 2018