{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T02:04:52Z","timestamp":1777341892196,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589334.3645608","type":"proceedings-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T07:08:13Z","timestamp":1715152093000},"page":"861-869","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Adversarial Mask Explainer for Graph Neural Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4317-1718","authenticated-orcid":false,"given":"Wei","family":"Zhang","sequence":"first","affiliation":[{"name":"L3S Research Center, Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4379-3277","authenticated-orcid":false,"given":"Xiaofan","family":"Li","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3374-2193","authenticated-orcid":false,"given":"Wolfgang","family":"Nejdl","sequence":"additional","affiliation":[{"name":"L3S Research Center, Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Search-Convolutional Neural Networks. CoRR","author":"Atwood James","year":"2015","unstructured":"James Atwood and Don Towsley. 2015. Search-Convolutional Neural Networks. CoRR , Vol. abs\/1511.02136 (2015). showeprint[arXiv]1511.02136 http:\/\/arxiv.org\/abs\/1511.02136"},{"key":"e_1_3_2_2_2_1","volume-title":"Explainability Techniques for Graph Convolutional Networks. CoRR","author":"Baldassarre Federico","year":"2019","unstructured":"Federico Baldassarre and Hossein Azizpour. 2019. Explainability Techniques for Graph Convolutional Networks. CoRR , Vol. abs\/1905.13686 (2019). showeprint[arXiv]1905.13686 http:\/\/arxiv.org\/abs\/1905.13686"},{"key":"e_1_3_2_2_3_1","unstructured":"Joan Bruna Wojciech Zaremba Arthur Szlam and Yann LeCun. 2014. Spectral Networks and Locally Connected Networks on Graphs. arxiv: 1312.6203 [cs.LG]"},{"key":"e_1_3_2_2_4_1","volume-title":"Jordan","author":"Chen Jianbo","year":"2018","unstructured":"Jianbo Chen, Le Song, Martin J. Wainwright, and Michael I. Jordan. 2018. Learning to Explain: An Information-Theoretic Perspective on Model Interpretation. CoRR , Vol. abs\/1802.07814 (2018). showeprint[arXiv]1802.07814 http:\/\/arxiv.org\/abs\/1802.07814"},{"key":"e_1_3_2_2_5_1","volume-title":"Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. CoRR","author":"Defferrard Micha\u00eb","year":"2016","unstructured":"Micha\u00eb l Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. CoRR , Vol. abs\/1606.09375 (2016). showeprint[arXiv]1606.09375 http:\/\/arxiv.org\/abs\/1606.09375"},{"key":"e_1_3_2_2_6_1","volume-title":"Timothy Hirzel, Al\u00e1 n Aspuru-Guzik, and Ryan P. Adams.","author":"Duvenaud David","year":"2015","unstructured":"David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael G\u00f3 mez-Bombarelli, Timothy Hirzel, Al\u00e1 n Aspuru-Guzik, and Ryan P. Adams. 2015. Convolutional Networks on Graphs for Learning Molecular Fingerprints. CoRR , Vol. abs\/1509.09292 (2015). showeprint[arXiv]1509.09292 http:\/\/arxiv.org\/abs\/1509.09292"},{"key":"e_1_3_2_2_7_1","volume-title":"Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. CoRR","author":"Funke Thorben","year":"2021","unstructured":"Thorben Funke, Megha Khosla, and Avishek Anand. 2021. Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. CoRR , Vol. abs\/2105.08621 (2021). showeprint[arXiv]2105.08621 https:\/\/arxiv.org\/abs\/2105.08621"},{"key":"e_1_3_2_2_8_1","volume-title":"Explaining Deep Learning Models - A Bayesian Non-parametric Approach. CoRR","author":"Guo Wenbo","year":"2018","unstructured":"Wenbo Guo, Sui Huang, Yunzhe Tao, Xinyu Xing, and Lin Lin. 2018. Explaining Deep Learning Models - A Bayesian Non-parametric Approach. CoRR , Vol. abs\/1811.03422 (2018). showeprint[arXiv]1811.03422 http:\/\/arxiv.org\/abs\/1811.03422"},{"key":"e_1_3_2_2_9_1","unstructured":"William L. Hamilton Rex Ying and Jure Leskovec. 2018. Inductive Representation Learning on Large Graphs. arxiv: 1706.02216 [cs.SI]"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_2_11_1","volume-title":"GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks. CoRR","author":"Huang Qiang","year":"2020","unstructured":"Qiang Huang, Makoto Yamada, Yuan Tian, Dinesh Singh, Dawei Yin, and Yi Chang. 2020. GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks. CoRR , Vol. abs\/2001.06216 (2020). showeprint[arXiv]2001.06216 https:\/\/arxiv.org\/abs\/2001.06216"},{"key":"e_1_3_2_2_12_1","unstructured":"Eric Jang Shixiang Gu and Ben Poole. 2017. Categorical Reparameterization with Gumbel-Softmax. arxiv: 1611.01144 [stat.ML]"},{"key":"e_1_3_2_2_13_1","volume-title":"Jaakkola","author":"Jin Wengong","year":"2020","unstructured":"Wengong Jin, Regina Barzilay, and Tommi S. Jaakkola. 2020. Composing Molecules with Multiple Property Constraints. CoRR , Vol. abs\/2002.03244 (2020). showeprint[arXiv]2002.03244 https:\/\/arxiv.org\/abs\/2002.03244"},{"key":"e_1_3_2_2_14_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2016","unstructured":"Thomas N. Kipf and Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. CoRR , Vol. abs\/1609.02907 (2016). showeprint[arXiv]1609.02907 http:\/\/arxiv.org\/abs\/1609.02907"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"e_1_3_2_2_16_1","volume-title":"abs\/1707.01154","author":"Lakkaraju Himabindu","year":"2017","unstructured":"Himabindu Lakkaraju, Ece Kamar, Rich Caruana, and Jure Leskovec. 2017. Interpretable & Explorable Approximations of Black Box Models. CoRR , Vol. abs\/1707.01154 (2017). showeprint[arXiv]1707.01154 http:\/\/arxiv.org\/abs\/1707.01154"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICACT.2014.6779106"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Wanyu Lin Hao Lan Hao Wang and Baochun Li. 2022. OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks. arxiv: 2203.15209 [cs.LG]","DOI":"10.1109\/CVPR52688.2022.01336"},{"key":"e_1_3_2_2_19_1","volume-title":"Lundberg and Su-In Lee","author":"Scott","year":"2017","unstructured":"Scott M. Lundberg and Su-In Lee. 2017. A unified approach to interpreting model predictions. CoRR , Vol. abs\/1705.07874 (2017). showeprint[arXiv]1705.07874 http:\/\/arxiv.org\/abs\/1705.07874"},{"key":"e_1_3_2_2_20_1","volume-title":"Parameterized Explainer for Graph Neural Network. CoRR","author":"Luo Dongsheng","year":"2020","unstructured":"Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, and Xiang Zhang. 2020. Parameterized Explainer for Graph Neural Network. CoRR , Vol. abs\/2011.04573 (2020). showeprint[arXiv]2011.04573 https:\/\/arxiv.org\/abs\/2011.04573"},{"key":"e_1_3_2_2_21_1","volume-title":"The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables. CoRR","author":"Maddison Chris J.","year":"2016","unstructured":"Chris J. Maddison, Andriy Mnih, and Yee Whye Teh. 2016. The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables. CoRR , Vol. abs\/1611.00712 (2016). showeprint[arXiv]1611.00712 http:\/\/arxiv.org\/abs\/1611.00712"},{"key":"e_1_3_2_2_22_1","volume-title":"Molecular geometry prediction using a deep generative graph neural network. CoRR","author":"Mansimov Elman","year":"2019","unstructured":"Elman Mansimov, Omar Mahmood, Seokho Kang, and Kyunghyun Cho. 2019. Molecular geometry prediction using a deep generative graph neural network. CoRR , Vol. abs\/1904.00314 (2019). showeprint[arXiv]1904.00314 http:\/\/arxiv.org\/abs\/1904.00314"},{"key":"e_1_3_2_2_23_1","volume-title":"Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. CoRR","author":"Miao Siqi","year":"2022","unstructured":"Siqi Miao, Miaoyuan Liu, and Pan Li. 2022. Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. CoRR , Vol. abs\/2201.12987 (2022). showeprint[arXiv]2201.12987 https:\/\/arxiv.org\/abs\/2201.12987"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01103"},{"key":"e_1_3_2_2_25_1","volume-title":"Explaining the Predictions of Any Classifier. CoRR","author":"Ribeiro Marco T\u00fa","year":"2016","unstructured":"Marco T\u00fa lio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016. \"Why Should I Trust You?\": Explaining the Predictions of Any Classifier. CoRR , Vol. abs\/1602.04938 (2016). showeprint[arXiv]1602.04938 http:\/\/arxiv.org\/abs\/1602.04938"},{"key":"e_1_3_2_2_26_1","volume-title":"Nicola De Cao, and Ivan Titov","author":"Schlichtkrull Michael Sejr","year":"2020","unstructured":"Michael Sejr Schlichtkrull, Nicola De Cao, and Ivan Titov. 2020. Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking. CoRR , Vol. abs\/2010.00577 (2020). showeprint[arXiv]2010.00577 https:\/\/arxiv.org\/abs\/2010.00577"},{"key":"e_1_3_2_2_27_1","volume-title":"Klaus-Robert M\u00fc ller, and Gr\u00e9 goire Montavon.","author":"Schnake Thomas","year":"2020","unstructured":"Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Sch\u00fc tt, Klaus-Robert M\u00fc ller, and Gr\u00e9 goire Montavon. 2020. XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks. CoRR , Vol. abs\/2006.03589 (2020). showeprint[arXiv]2006.03589 https:\/\/arxiv.org\/abs\/2006.03589"},{"key":"e_1_3_2_2_28_1","volume-title":"Layerwise Relevance Visualization in Convolutional Text Graph Classifiers. arxiv","author":"Schwarzenberg Robert","year":"1909","unstructured":"Robert Schwarzenberg, Marc H\u00fcbner, David Harbecke, Christoph Alt, and Leonhard Hennig. 2019. Layerwise Relevance Visualization in Convolutional Text Graph Classifiers. arxiv: 1909.10911 [cs.CL]"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature24270"},{"key":"e_1_3_2_2_30_1","volume-title":"Causal Attention for Interpretable and Generalizable Graph Classification. CoRR","author":"Sui Yongduo","year":"2021","unstructured":"Yongduo Sui, Xiang Wang, Jiancan Wu, Xiangnan He, and Tat-Seng Chua. 2021. Causal Attention for Interpretable and Generalizable Graph Classification. CoRR , Vol. abs\/2112.15089 (2021). showeprint[arXiv]2112.15089 https:\/\/arxiv.org\/abs\/2112.15089"},{"key":"e_1_3_2_2_31_1","volume-title":"Axiomatic Attribution for Deep Networks. CoRR","author":"Sundararajan Mukund","year":"2017","unstructured":"Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017. Axiomatic Attribution for Deep Networks. CoRR , Vol. abs\/1703.01365 (2017). showeprint[arXiv]1703.01365 http:\/\/arxiv.org\/abs\/1703.01365"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511948"},{"key":"e_1_3_2_2_33_1","volume-title":"ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units using Chebyshev Approximations. CoRR","author":"Tang Shanshan","year":"2019","unstructured":"Shanshan Tang, Bo Li, and Haijun Yu. 2019. ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units using Chebyshev Approximations. CoRR , Vol. abs\/1911.05467 (2019). showeprint[arXiv]1911.05467 http:\/\/arxiv.org\/abs\/1911.05467"},{"key":"e_1_3_2_2_34_1","unstructured":"Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018. Graph Attention Networks. arxiv: 1710.10903 [stat.ML]"},{"key":"e_1_3_2_2_35_1","volume-title":"Thai","author":"Vu Minh N.","year":"2020","unstructured":"Minh N. Vu and My T. Thai. 2020. PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks. CoRR , Vol. abs\/2010.05788 (2020). showeprint[arXiv]2010.05788 https:\/\/arxiv.org\/abs\/2010.05788"},{"key":"e_1_3_2_2_36_1","volume-title":"Webb","author":"Wang Chi-Jen","year":"2018","unstructured":"Chi-Jen Wang, Seokjoo Chae, Leonid A. Bunimovich, and Benjamin Z. Webb. 2018. Uncovering Hierarchical Structure in Social Networks using Isospectral Reductions. CoRR , Vol. abs\/1801.03385 (2018). showeprint[arXiv]1801.03385 http:\/\/arxiv.org\/abs\/1801.03385"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467451"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.5555\/3367471.3367590"},{"key":"e_1_3_2_2_39_1","volume-title":"GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks. CoRR","author":"Ying Rex","year":"2019","unstructured":"Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, and Jure Leskovec. 2019. GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks. CoRR , Vol. abs\/1903.03894 (2019). showeprint[arXiv]1903.03894 http:\/\/arxiv.org\/abs\/1903.03894"},{"key":"e_1_3_2_2_40_1","volume-title":"Improving Subgraph Recognition with Variational Graph Information Bottleneck. CoRR","author":"Yu Junchi","year":"2021","unstructured":"Junchi Yu, Jie Cao, and Ran He. 2021. Improving Subgraph Recognition with Variational Graph Information Bottleneck. CoRR , Vol. abs\/2112.09899 (2021). showeprint[arXiv]2112.09899 https:\/\/arxiv.org\/abs\/2112.09899"},{"key":"e_1_3_2_2_41_1","volume-title":"Graph Information Bottleneck for Subgraph Recognition. CoRR","author":"Yu Junchi","year":"2020","unstructured":"Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, and Ran He. 2020. Graph Information Bottleneck for Subgraph Recognition. CoRR , Vol. abs\/2010.05563 (2020). showeprint[arXiv]2010.05563 https:\/\/arxiv.org\/abs\/2010.05563"},{"key":"e_1_3_2_2_42_1","volume-title":"On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR","author":"Yuan Hao","year":"2021","unstructured":"Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, and Shuiwang Ji. 2021. On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR , Vol. abs\/2102.05152 (2021). showeprint[arXiv]2102.05152 https:\/\/arxiv.org\/abs\/2102.05152"},{"key":"e_1_3_2_2_43_1","volume-title":"Zeiler and Rob Fergus","author":"Matthew","year":"2013","unstructured":"Matthew D. Zeiler and Rob Fergus. 2013. Visualizing and Understanding Convolutional Networks. CoRR , Vol. abs\/1311.2901 (2013). showeprint[arXiv]1311.2901 http:\/\/arxiv.org\/abs\/1311.2901"},{"key":"e_1_3_2_2_44_1","volume-title":"Link Prediction Based on Graph Neural Networks. CoRR","author":"Zhang Muhan","year":"2018","unstructured":"Muhan Zhang and Yixin Chen. 2018. Link Prediction Based on Graph Neural Networks. CoRR , Vol. abs\/1802.09691 (2018). showeprint[arXiv]1802.09691 http:\/\/arxiv.org\/abs\/1802.09691 io"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645608","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589334.3645608","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:31:37Z","timestamp":1755822697000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645608"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":44,"alternative-id":["10.1145\/3589334.3645608","10.1145\/3589334"],"URL":"https:\/\/doi.org\/10.1145\/3589334.3645608","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}