Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study

International Conference on Intelligent User Interfaces (IUI), 2020

3 February 2020

Papers citing "Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study"

50 / 90 papers shown

Title
From Prediction to Explanation: Multimodal, Explainable, and Interactive Deepfake Detection Framework for Non-Expert Users Shahroz Tariq Simon S. Woo Priyanka Singh Irena Irmalasari Saakshi Gupta Dev Gupta 95 2 0 11 Aug 2025
CASE: Contrastive Activation for Saliency Estimation Dane Williamson Yangfeng Ji Matthew B. Dwyer FAtt AAML 289 0 0 08 Jun 2025
Multi-Domain Explainability of Preferences Nitay Calderon Liat Ein-Dor Roi Reichart LRM 262 0 0 26 May 2025
Explanation User Interfaces: A Systematic Literature Review Eleonora Cappuccio Andrea Esposito Francesco Greco Giuseppe Desolda Rosa Lanzilotti Salvatore Rinzivillo 235 0 0 26 May 2025
Evaluating Model Explanations without Ground TruthConference on Fairness, Accountability and Transparency (FAccT), 2025 Kaivalya Rawal Zihao Fu Eoin Delaney Chris Russell FAtt XAI 261 1 0 15 May 2025
What Do People Want to Know About Artificial Intelligence (AI)? The Importance of Answering End-User Questions to Explain Autonomous Vehicle (AV) DecisionsProceedings of the ACM on Human-Computer Interaction (PACMHCI), 2025 Somayeh Molaei Lionel P. Robert Nikola Banovic 129 0 0 09 May 2025
What Makes for a Good Saliency Map? Comparing Strategies for Evaluating Saliency Maps in Explainable AI (XAI) Felix Kares Timo Speith Hanwei Zhang Markus Langer FAtt XAI 303 4 0 23 Apr 2025
From Abstract to Actionable: Pairwise Shapley Values for Explainable AI Jiaxin Xu Hung Chau Angela Burden TDI 314 2 0 18 Feb 2025
Identifying Bias in Deep Neural Networks Using Image TransformsDe Computis (DC), 2024 Sai Teja Erukude Akhil Joshi Lior Shamir 173 5 0 17 Dec 2024
Towards Human-centered Design of Explainable Artificial Intelligence (XAI): A Survey of Empirical Studies Shuai Ma 202 5 0 28 Oct 2024
Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support SettingConference on Empirical Methods in Natural Language Processing (EMNLP), 2024 Maxime Kayser Bayar I. Menzat Cornelius Emde Bogdan Bercean Alex Novak Abdala Espinosa B. Papież Susanne Gaube Thomas Lukasiewicz Oana-Maria Camburu 353 10 0 16 Oct 2024
Explainable AI Reloaded: Challenging the XAI Status Quo in the Era of Large Language Models Upol Ehsan Mark O. Riedl 208 7 0 09 Aug 2024
Automatic rating of incomplete hippocampal inversions evaluated across multiple cohortsMachine Learning for Biomedical Imaging (MLBI), 2024 Lisa Hemforth B. Couvy-Duchesne Kevin de Matos Camille Brianceau Matthieu Joulot ... V. Frouin Alexandre Martin IMAGEN study group C. Cury O. Colliot 184 1 0 05 Aug 2024
On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs Nitay Calderon Roi Reichart 302 23 0 27 Jul 2024
Graphical Perception of Saliency-based Model Explanations Yayan Zhao Mingwei Li Matthew Berger XAI FAtt 238 2 0 11 Jun 2024
The AI-DEC: A Card-based Design Method for User-centered AI Explanations Christine P. Lee M. Lee Bilge Mutlu HAI 193 9 0 26 May 2024
Explaining Multi-modal Large Language Models by Analyzing their Vision PerceptionBritish Machine Vision Conference (BMVC), 2024 Loris Giulivi Giacomo Boracchi 146 3 0 23 May 2024
Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNetIEEE International Joint Conference on Neural Network (IJCNN), 2024 Loris Giulivi Giacomo Boracchi 165 2 0 23 May 2024
Unraveling the Dilemma of AI Errors: Exploring the Effectiveness of Human and Machine Explanations for Large Language Models Marvin Pafla Kate Larson Mark Hancock 165 7 0 11 Apr 2024
How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency mapsInternational journal of human computer interactions (IJHCI), 2024 Romy Müller HAI 188 12 0 03 Apr 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningCognitive Systems Research (Cogn. Syst. Res.), 2023 F. Mumuni A. Mumuni AAML 258 16 0 11 Mar 2024
Can Interpretability Layouts Influence Human Perception of Offensive Sentences? Thiago Freitas dos Santos Nardine Osman Marco Schorlemmer 153 0 0 01 Mar 2024
Reimagining Anomalies: What If Anomalies Were Normal? Philipp Liznerski Saurabh Varshneya Ece Calikus Sophie Fellenz Matthias Kirchler 166 4 0 22 Feb 2024
OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning Jiaqi Ma Vivian Lai Yiming Zhang Chacha Chen Paul Hamilton Davor Ljubenkov Himabindu Lakkaraju Chenhao Tan ELM 140 3 0 20 Feb 2024
Explaining Time Series via Contrastive and Locally Sparse PerturbationsInternational Conference on Learning Representations (ICLR), 2024 Zichuan Liu Yingying Zhang Tianchun Wang Zefan Wang Dongsheng Luo ... Min Wu Yi Wang Chunlin Chen Lunting Fan Qingsong Wen 306 19 0 16 Jan 2024
Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-assisted Decision MakingAAAI Conference on Artificial Intelligence (AAAI), 2024 Zhuoyan Li Zhuoran Lu Ming Yin 150 21 0 11 Jan 2024
ALMANACS: A Simulatability Benchmark for Language Model Explainability Edmund Mills Shiye Su Stuart J. Russell Scott Emmons 449 9 0 20 Dec 2023
Error Discovery by Clustering Influence EmbeddingsNeural Information Processing Systems (NeurIPS), 2023 Fulton Wang Julius Adebayo Sarah Tan Diego Garcia-Olano Narine Kokhlikyan 270 5 0 07 Dec 2023
Understanding Parameter Saliency via Extreme Value Theory Shuo Wang Issei Sato AAML FAtt 163 0 0 27 Oct 2023
Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis Anahid N. Jalali Bernhard Haslhofer Simone Kriglstein Andreas Rauber FAtt 239 6 0 21 Sep 2023
TExplain: Explaining Learned Visual Features via Pre-trained (Frozen) Language Models Saeid Asgari Taghanaki Aliasghar Khani Ali Saheb Pasand Amir Khasahmadi Aditya Sanghi K. Willis Ali Mahdavi-Amiri FAtt VLM 119 0 0 01 Sep 2023
FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security AnalysisConference on Computer and Communications Security (CCS), 2023 Yiling He Jian Lou Zhan Qin Kui Ren FAtt AAML 152 14 0 10 Aug 2023
Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making Min Hun Lee Chong Jun Chew 187 51 0 08 Aug 2023
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural NetworksKnowledge Discovery and Data Mining (KDD), 2023 Gao Li M. Duda Xinming Zhang Danai Koutra Yujun Yan 186 15 0 26 Jun 2023
Towards Robust Aspect-based Sentiment Analysis through Non-counterfactual Augmentations Xinyu Liu Yanl Ding Kaikai An Chunyang Xiao Pranava Madhyastha Tong Xiao Jingbo Zhu 125 2 0 24 Jun 2023
In Search of Verifiability: Explanations Rarely Enable Complementary Performance in AI-Advised Decision MakingThe AI Magazine (AI Mag.), 2023 Raymond Fok Daniel S. Weld 293 82 0 12 May 2023
Multimodal Understanding Through Correlation Maximization and Minimization Yi Shi Marc Niethammer 150 1 0 04 May 2023
Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UKConference on Fairness, Accountability and Transparency (FAccT), 2023 L. Nannini Agathe Balayn A. Smith 230 50 0 20 Apr 2023
Performance of GAN-based augmentation for deep learning COVID-19 image classification Oleksandr Fedoruk Konrad Klimaszewski Aleksander Ogonowski Rafal Mo.zd.zonek OOD MedIm 152 15 0 18 Apr 2023
How good Neural Networks interpretation methods really are? A quantitative benchmark Antoine Passemiers Pietro Folco D. Raimondi G. Birolo Yves Moreau P. Fariselli FAtt 108 2 0 05 Apr 2023
Model-agnostic explainable artificial intelligence for object detection in image dataEngineering applications of artificial intelligence (Eng. Appl. Artif. Intell.), 2023 M. Moradi Ke Yan David Colwell Matthias Samwald Rhona Asgari AAML 178 10 0 30 Mar 2023
IRIS: Interpretable Rubric-Informed Segmentation for Action Quality AssessmentInternational Conference on Intelligent User Interfaces (IUI), 2023 Hitoshi Matsuyama Nobuo Kawaguchi Brian Y. Lim 112 9 0 16 Mar 2023
The Generalizability of ExplanationsIEEE International Joint Conference on Neural Network (IJCNN), 2023 Hanxiao Tan FAtt 121 1 0 23 Feb 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function ProposalACM Transactions on Intelligent Systems and Technology (ACM TIST), 2023 M. Hashemi Ali Darejeh Francisco Cruz 301 4 0 07 Feb 2023
Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAI Upol Ehsan Koustuv Saha M. D. Choudhury Mark O. Riedl 216 72 0 01 Feb 2023
Explainable Deep Reinforcement Learning: State of the Art and ChallengesACM Computing Surveys (ACM CSUR), 2022 G. Vouros XAI 317 116 0 24 Jan 2023
On the Relationship Between Explanation and Prediction: A Causal ViewInternational Conference on Machine Learning (ICML), 2022 Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 315 16 0 13 Dec 2022
Post hoc Explanations may be Ineffective for Detecting Unknown Spurious CorrelationInternational Conference on Learning Representations (ICLR), 2022 Julius Adebayo M. Muelly H. Abelson Been Kim 197 93 0 09 Dec 2022
A Rigorous Study Of The Deep Taylor Decomposition Leon Sixt Tim Landgraf FAtt AAML 117 7 0 14 Nov 2022
Towards Human-centered Explainable AI: A Survey of User Studies for Model ExplanationsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Yao Rong Tobias Leemann Thai-trang Nguyen Lisa Fiedler Peizhu Qian Vaibhav Unhelkar Tina Seidel Gjergji Kasneci Enkelejda Kasneci ELM 250 153 0 20 Oct 2022